201
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Wigdor EM, Weiner DJ, Grove J, Fu JM, Thompson WK, Carey CE, Baya N, van der Merwe C, Walters RK, Satterstrom FK, Palmer DS, Rosengren A, Bybjerg-Grauholm J, Hougaard DM, Mortensen PB, Daly MJ, Talkowski ME, Sanders SJ, Bishop SL, Børglum AD, Robinson EB. The female protective effect against autism spectrum disorder. CELL GENOMICS 2022; 2:100134. [PMID: 36778135 PMCID: PMC9903803 DOI: 10.1016/j.xgen.2022.100134] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 02/26/2022] [Accepted: 04/27/2022] [Indexed: 12/20/2022]
Abstract
Autism spectrum disorder (ASD) is diagnosed three to four times more frequently in males than in females. Genetic studies of rare variants support a female protective effect (FPE) against ASD. However, sex differences in common inherited genetic risk for ASD are less studied, particularly within families. Leveraging the Danish iPSYCH resource, we found siblings of female ASD cases (n = 1,707) had higher rates of ASD than siblings of male ASD cases (n = 6,270; p < 1.0 × 10-10). In the Simons Simplex and SPARK collections, mothers of ASD cases (n = 7,436) carried more polygenic risk for ASD than fathers of ASD cases (n = 5,926; 0.08 polygenic risk score [PRS] SD; p = 7.0 × 10-7). Further, male unaffected siblings under-inherited polygenic risk (n = 1,519; p = 0.03). Using both epidemiologic and genetic approaches, our findings strongly support an FPE against ASD's common inherited influences.
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Affiliation(s)
- Emilie M. Wigdor
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
| | - Daniel J. Weiner
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jakob Grove
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, 8000 Aarhus, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, 8000 Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
| | - Jack M. Fu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Caitlin E. Carey
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Nikolas Baya
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Celia van der Merwe
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Raymond K. Walters
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - F. Kyle Satterstrom
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Duncan S. Palmer
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Anders Rosengren
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct Hans, Copenhagen University Hospital, 4000 Roskilde, Denmark
| | - Jonas Bybjerg-Grauholm
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen, Denmark
| | | | - David M. Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen, Denmark
| | - Preben Bo Mortensen
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, 8000 Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct Hans, Copenhagen University Hospital, 4000 Roskilde, Denmark
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark
- Center for Integrated Register-based Research, Aarhus University, 8210 Aarhus, Denmark
| | - Mark J. Daly
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Finnish Institute for Molecular Medicine, University of Helsinki, 00290 Helsinki, Finland
| | - Michael E. Talkowski
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Stephan J. Sanders
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Somer L. Bishop
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Anders D. Børglum
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, 8000 Aarhus, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, 8000 Aarhus, Denmark
- Institute of Biological Psychiatry, MHC Sct Hans, Copenhagen University Hospital, 4000 Roskilde, Denmark
| | - Elise B. Robinson
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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202
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Mallard TT, Karlsson Linnér R, Grotzinger AD, Sanchez-Roige S, Seidlitz J, Okbay A, de Vlaming R, Meddens SFW, Palmer AA, Davis LK, Tucker-Drob EM, Kendler KS, Keller MC, Koellinger PD, Harden KP. Multivariate GWAS of psychiatric disorders and their cardinal symptoms reveal two dimensions of cross-cutting genetic liabilities. CELL GENOMICS 2022; 2:S2666-979X(22)00073-8. [PMID: 35812988 PMCID: PMC9264403 DOI: 10.1016/j.xgen.2022.100140] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 10/25/2021] [Accepted: 05/10/2022] [Indexed: 02/07/2023]
Abstract
Understanding which biological pathways are specific versus general across diagnostic categories and levels of symptom severity is critical to improving nosology and treatment of psychopathology. Here, we combine transdiagnostic and dimensional approaches to genetic discovery for the first time, conducting a novel multivariate genome-wide association study of eight psychiatric symptoms and disorders broadly related to mood disturbance and psychosis. We identify two transdiagnostic genetic liabilities that distinguish between common forms of psychopathology versus rarer forms of serious mental illness. Biological annotation revealed divergent genetic architectures that differentially implicated prenatal neurodevelopment and neuronal function and regulation. These findings inform psychiatric nosology and biological models of psychopathology, as they suggest that the severity of mood and psychotic symptoms present in serious mental illness may reflect a difference in kind rather than merely in degree.
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Affiliation(s)
- Travis T. Mallard
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Richard Karlsson Linnér
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Autism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, USA
| | | | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ronald de Vlaming
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - S. Fleur W. Meddens
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Bipolar Disorder Working Group of the Psychiatric Genomics Consortium
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Autism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Medical College of Virginia/Virginia Commonwealth University, Richmond, VA, USA
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Abraham A. Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Lea K. Davis
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Elliot M. Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Medical College of Virginia/Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew C. Keller
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Philipp D. Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - K. Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
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203
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Guo MH, Sama P, LaBarre BA, Lokhande H, Balibalos J, Chu C, Du X, Kheradpour P, Kim CC, Oniskey T, Snyder T, Soghoian DZ, Weiner HL, Chitnis T, Patsopoulos NA. Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets. Genome Biol 2022; 23:127. [PMID: 35672799 PMCID: PMC9175345 DOI: 10.1186/s13059-022-02694-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 05/16/2022] [Indexed: 11/10/2022] Open
Abstract
Background Multiple sclerosis (MS) is an autoimmune condition of the central nervous system with a well-characterized genetic background. Prior analyses of MS genetics have identified broad enrichments across peripheral immune cells, yet the driver immune subsets are unclear. Results We utilize chromatin accessibility data across hematopoietic cells to identify cell type-specific enrichments of MS genetic signals. We find that CD4 T and B cells are independently enriched for MS genetics and further refine the driver subsets to Th17 and memory B cells, respectively. We replicate our findings in data from untreated and treated MS patients and find that immunomodulatory treatments suppress chromatin accessibility at driver cell types. Integration of statistical fine-mapping and chromatin interactions nominate numerous putative causal genes, illustrating complex interplay between shared and cell-specific genes. Conclusions Overall, our study finds that open chromatin regions in CD4 T cells and B cells independently drive MS genetic signals. Our study highlights how careful integration of genetics and epigenetics can provide fine-scale insights into causal cell types and nominate new genes and pathways for disease. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-022-02694-y.
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204
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Sorokin EP, Basty N, Whitcher B, Liu Y, Bell JD, Cohen RL, Cule M, Thomas EL. Analysis of MRI-derived spleen iron in the UK Biobank identifies genetic variation linked to iron homeostasis and hemolysis. Am J Hum Genet 2022; 109:1092-1104. [PMID: 35568031 PMCID: PMC9247824 DOI: 10.1016/j.ajhg.2022.04.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 04/19/2022] [Indexed: 11/25/2022] Open
Abstract
The spleen plays a key role in iron homeostasis. It is the largest filter of the blood and performs iron reuptake from old or damaged erythrocytes. Despite this role, spleen iron concentration has not been measured in a large, population-based cohort. In this study, we quantify spleen iron in 41,764 participants of the UK Biobank by using magnetic resonance imaging and provide a reference range for spleen iron in an unselected population. Through genome-wide association study, we identify associations between spleen iron and regulatory variation at two hereditary spherocytosis genes, ANK1 and SPTA1. Spherocytosis-causing coding mutations in these genes are associated with lower reticulocyte volume and increased reticulocyte percentage, while these common alleles are associated with increased expression of ANK1 and SPTA1 in blood and with larger reticulocyte volume and reduced reticulocyte percentage. As genetic modifiers, these common alleles may explain mild spherocytosis phenotypes that have been observed clinically. Our genetic study also identifies a signal that co-localizes with a splicing quantitative trait locus for MS4A7, and we show this gene is abundantly expressed in the spleen and in macrophages. The combination of deep learning and efficient image processing enables non-invasive measurement of spleen iron and, in turn, characterization of genetic factors related to the lytic phase of the erythrocyte life cycle and iron reuptake in the spleen.
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Affiliation(s)
| | - Nicolas Basty
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | - Brandon Whitcher
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | - Yi Liu
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | - Jimmy D Bell
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | | | | | - E Louise Thomas
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
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205
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Huang L, Rosen JD, Sun Q, Chen J, Wheeler MM, Zhou Y, Min YI, Kooperberg C, Conomos MP, Stilp AM, Rich SS, Rotter JI, Manichaikul A, Loos RJF, Kenny EE, Blackwell TW, Smith AV, Jun G, Sedlazeck FJ, Metcalf G, Boerwinkle E, Raffield LM, Reiner AP, Auer PL, Li Y. TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data. Am J Hum Genet 2022; 109:1175-1181. [PMID: 35504290 PMCID: PMC9247832 DOI: 10.1016/j.ajhg.2022.04.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 04/08/2022] [Indexed: 01/07/2023] Open
Abstract
Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.
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Affiliation(s)
- Le Huang
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jonathan D Rosen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Marsha M Wheeler
- Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA
| | - Ying Zhou
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Yuan-I Min
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Eimear E Kenny
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Thomas W Blackwell
- TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109, USA
| | - Albert V Smith
- TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109, USA
| | - Goo Jun
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ginger Metcalf
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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206
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de la Fuente J, Grotzinger AD, Marioni RE, Nivard MG, Tucker-Drob EM. Integrated analysis of direct and proxy genome wide association studies highlights polygenicity of Alzheimer's disease outside of the APOE region. PLoS Genet 2022; 18:e1010208. [PMID: 35658006 PMCID: PMC9200312 DOI: 10.1371/journal.pgen.1010208] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 06/15/2022] [Accepted: 04/19/2022] [Indexed: 11/19/2022] Open
Abstract
Recent meta-analyses combining direct genome-wide association studies (GWAS) with those of family history (GWAX) have indicated very low SNP heritability of Alzheimer's disease (AD). These low estimates may call into question the prospects of continued progress in genetic discovery for AD within the spectrum of common variants. We highlight dramatic downward biases in previous methods, and we validate a novel method for the estimation of SNP heritability via integration of GWAS and GWAX summary data. We apply our method to investigate the genetic architecture of AD using GWAX from UK Biobank and direct case-control GWAS from the International Genomics of Alzheimer's Project (IGAP). We estimate the liability scale common variant SNP heritability of Clinical AD outside of APOE region at ~7-11%, and we project the corresponding estimate for AD pathology to be up to approximately 23%. We estimate that nearly 90% of common variant SNP heritability of Clinical AD exists outside the APOE region. Rare variants not tagged in standard GWAS may account for additional variance. Our results indicate that, while GWAX for AD in UK Biobank may result in greater attenuation of genetic effects beyond that conventionally assumed, it does not introduce appreciable contamination of signal by genetically distinct traits relative to direct case-control GWAS in IGAP. Genetic risk for AD represents a strong effect of APOE superimposed upon a highly polygenic background.
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Affiliation(s)
- Javier de la Fuente
- Department of Psychology, University of Texas at Austin, Texas, United States of America
- Population Research Center and Center on Aging and Population Sciences, University of Texas at Austin, Texas, United States of America
- * E-mail: (JF); (EMT-D)
| | - Andrew D. Grotzinger
- Department of Psychology, University of Texas at Austin, Texas, United States of America
- Psychiatric and Neurodevelopmental Genetics Unit (PNGU) and the Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, United Kingdom
| | - Michel G. Nivard
- Department of Biological Psychology, VU University Amsterdam, the Netherlands
| | - Elliot M. Tucker-Drob
- Department of Psychology, University of Texas at Austin, Texas, United States of America
- Population Research Center and Center on Aging and Population Sciences, University of Texas at Austin, Texas, United States of America
- * E-mail: (JF); (EMT-D)
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207
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Temprano-Sagrera G, Sitlani CM, Bone WP, Martin-Bornez M, Voight BF, Morrison AC, Damrauer SM, de Vries PS, Smith NL, Sabater-Lleal M. Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations. J Thromb Haemost 2022; 20:1331-1349. [PMID: 35285134 PMCID: PMC9314075 DOI: 10.1111/jth.15698] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 02/15/2022] [Accepted: 03/08/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. OBJECTIVES To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. METHODS Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10-9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). RESULTS Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. CONCLUSIONS The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.
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Affiliation(s)
- Gerard Temprano-Sagrera
- Genomics of Complex Disease Unit, Sant Pau Biomedical Research Institute. IIB-Sant Pau, Barcelona, Spain
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - William P Bone
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Miguel Martin-Bornez
- Genomics of Complex Disease Unit, Sant Pau Biomedical Research Institute. IIB-Sant Pau, Barcelona, Spain
| | - Benjamin F Voight
- Department of Systems Pharmacology and Translational Therapeutics and Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Scott M Damrauer
- Department of Surgery and Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente, Seattle, Washington, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, Washington, USA
| | - Maria Sabater-Lleal
- Genomics of Complex Disease Unit, Sant Pau Biomedical Research Institute. IIB-Sant Pau, Barcelona, Spain
- Cardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
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208
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Pirastu N, McDonnell C, Grzeszkowiak EJ, Mounier N, Imamura F, Merino J, Day FR, Zheng J, Taba N, Concas MP, Repetto L, Kentistou KA, Robino A, Esko T, Joshi PK, Fischer K, Ong KK, Gaunt TR, Kutalik Z, Perry JRB, Wilson JF. Using genetic variation to disentangle the complex relationship between food intake and health outcomes. PLoS Genet 2022; 18:e1010162. [PMID: 35653391 PMCID: PMC9162356 DOI: 10.1371/journal.pgen.1010162] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 03/22/2022] [Indexed: 02/02/2023] Open
Abstract
Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.
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Affiliation(s)
- Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Human Technopole, Milan, Italy
- * E-mail:
| | - Ciara McDonnell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Centre for Cardiovascular Sciences, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Eryk J. Grzeszkowiak
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ninon Mounier
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Fumiaki Imamura
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jordi Merino
- Diabetes Unit and Centre for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Felix R. Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jie Zheng
- MRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom
| | - Nele Taba
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Maria Pina Concas
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Linda Repetto
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Katherine A. Kentistou
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Centre for Cardiovascular Sciences, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Antonietta Robino
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Peter K. Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Krista Fischer
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom
| | - Zoltán Kutalik
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - John R. B. Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - James F. Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland, United Kingdom
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209
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Assessment of Bidirectional Relationships between Leisure Sedentary Behaviors and Neuropsychiatric Disorders: A Two-Sample Mendelian Randomization Study. Genes (Basel) 2022; 13:genes13060962. [PMID: 35741723 PMCID: PMC9223103 DOI: 10.3390/genes13060962] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 05/22/2022] [Accepted: 05/24/2022] [Indexed: 02/05/2023] Open
Abstract
(1) Background: Increasing evidence shows that sedentary behaviors are associated with neuropsychiatric disorders (NPDs) and thus may be a modifiable factor to target for the prevention of NPDs. However, the direction and causality for the relationship remain unknown; sedentary behaviors could increase or decrease the risk of NPDs, and/or NPDs may increase or decrease engagement in sedentary behaviors. (2) Methods: This Mendelian randomization (MR) study with two samples included independent genetic variants related to sedentary behaviors (n = 408,815), Alzheimer's disease (AD; n = 63,926), schizophrenia (SCZ; n = 105,318), and major depressive disorder (MDD; n = 500,199), which were extracted from several of the largest non-overlapping genome-wide association studies (GWASs), as instrumental variables. The summarized MR effect sizes from each instrumental variable were combined in an IVW (inverse-variance-weighted) approach, with various approaches (e.g., MR-Egger, weighted median, MR-pleiotropy residual sum and outlier), and sensitivity analyses were performed to identify and remove outliers and assess the horizontal pleiotropy. (3) Results: The MR evidence and linkage disequilibrium score regression revealed a consistent directional association between television watching and MDD (odds ratio (OR), 1.13 for MDD per one standard deviation (SD) increase in mean television watching time; 95% CI, 1.06-1.20; p = 6.80 × 10-5) and a consistent relationship between computer use and a decrease in the risk of AD (OR, 0.52 for AD per one SD increase in mean computer use time; 95% CI, 0.32-0.84; p = 8.20 × 10-3). In the reverse direction, MR showed a causal association between a reduced risk of SCZ and an increase in driving time (β, -0.016; 95% CI, -0.027--0.004; p = 8.30 × 10-3). (4) Conclusions: Using genetic instrumental variables identified from large-scale GWASs, we found robust evidence for a causal relationship between long computer use time and a reduced risk of AD, and for a causal relationship between long television watching time and an increased risk of MDD. In reverse analyses, we found that SCZ was causally associated with reduced driving time. These findings fit in with our observations and prior knowledge as well as emphasizing the importance of distinguishing between different domains of sedentary behaviors in epidemiologic studies of NPDs.
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210
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Ghatti S, Yoon E, Lopez G, Ehrlich D, Horovitz SG. Imaging and genetics in Parkinson's disease: assessment of the GBA1 mutation. J Neurol 2022; 269:5347-5355. [PMID: 35604467 PMCID: PMC10402751 DOI: 10.1007/s00415-022-11181-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 04/21/2022] [Accepted: 05/10/2022] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Several genetic variants are associated with an increased risk for developing Parkinson's Disease (PD) and limited genotype/phenotype correlation. Specifically, mutations in GBA1, the gene coding for the lysosomal enzyme glucocerebrosidase, are associated with an earlier age of onset and faster disease progression. Given these phenotypic differences associated with GBA1 variants, we explored whether cortical thickness and other biomarkers of neurodegeneration differed in healthy controls and PD patients with and without GBA1 variants. METHODS To understand how different GBA1 variants influence PD phenotype early in the disease, we retrieved neuroimaging and biospecimen data from the Parkinson's Progression Markers Initiative database. Using FreeSurfer, we compared T1-weighted MRI images from healthy controls (N = 47) to PD patients with heterozygous N370S (N = 21), heterozygous E326K (N = 18) or heterozygous T369M (N = 8) variants, and GBA1 non-mutation carriers (N = 47). RESULTS Cortical thickness in PD patients differed from controls in the parietal cortex, with E365K, T369M variants, and GBA1 non-mutation carriers showing more cortical thinning than N370S variants. Patients with N370S variants had significantly higher serum neurofilament light levels among all groups. CONCLUSION Our results demonstrate significant cortical thinning in PD patients independent of genotype in superior parietal and postcentral regions when compared to the controls. They highlight the impact of GBA1 variants on cortical thickness in the parietal cortex. Finally, they suggest that recently diagnosed PD patients with N370S variants have a higher cortical thickness and increased active neurodegeneration when compared to PD patients without GBA1 mutations and PD patients with E326K or T369M variants.
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Affiliation(s)
- Sweta Ghatti
- National Institutes of Neurological Disease and Stroke, Bethesda, MD, USA.
| | - Esther Yoon
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Grisel Lopez
- National Human Genome Research Institutes, Bethesda, MD, USA
| | - Debra Ehrlich
- National Institutes of Neurological Disease and Stroke, Bethesda, MD, USA
| | - Silvina G Horovitz
- National Institutes of Neurological Disease and Stroke, Bethesda, MD, USA
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211
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Kweon H, Aydogan G, Dagher A, Bzdok D, Ruff CC, Nave G, Farah MJ, Koellinger PD. Human brain anatomy reflects separable genetic and environmental components of socioeconomic status. SCIENCE ADVANCES 2022; 8:eabm2923. [PMID: 35584223 PMCID: PMC9116589 DOI: 10.1126/sciadv.abm2923] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Socioeconomic status (SES) correlates with brain structure, a relation of interest given the long-observed relations of SES to cognitive abilities and health. Yet, major questions remain open, in particular, the pattern of causality that underlies this relation. In an unprecedently large study, here, we assess genetic and environmental contributions to SES differences in neuroanatomy. We first establish robust SES-gray matter relations across a number of brain regions, cortical and subcortical. These regional correlates are parsed into predominantly genetic factors and those potentially due to the environment. We show that genetic effects are stronger in some areas (prefrontal cortex, insula) than others. In areas showing less genetic effect (cerebellum, lateral temporal), environmental factors are likely to be influential. Our results imply a complex interplay of genetic and environmental factors that influence the SES-brain relation and may eventually provide insights relevant to policy.
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Affiliation(s)
- Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands
| | - Gökhan Aydogan
- Zürich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, 8006 Zürich, Switzerland
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montreal Neurological Institute (MNI), McGill University, Montreal, QC H3A 2B4, Canada
| | - Danilo Bzdok
- McConnell Brain Imaging Centre, Montreal Neurological Institute (MNI), McGill University, Montreal, QC H3A 2B4, Canada
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, QC H3A 2B4, Canada
- School of Computer Science, McGill University, Montreal, QC H3A 2A7, Canada
- Mila-Quebec Artificial Intelligence Institute, Montreal, QC H2S 3H1, Canada
| | - Christian C. Ruff
- Zürich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, 8006 Zürich, Switzerland
| | - Gideon Nave
- Marketing Department, the Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Martha J. Farah
- Center for Neuroscience & Society, University of Pennsylvania, Philadelphia, PA 19104, USA
- Corresponding author. (M.J.F.); (P.D.K.)
| | - Philipp D. Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI 53706, USA
- Corresponding author. (M.J.F.); (P.D.K.)
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212
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May-Wilson S, Matoba N, Wade KH, Hottenga JJ, Concas MP, Mangino M, Grzeszkowiak EJ, Menni C, Gasparini P, Timpson NJ, Veldhuizen MG, de Geus E, Wilson JF, Pirastu N. Large-scale GWAS of food liking reveals genetic determinants and genetic correlations with distinct neurophysiological traits. Nat Commun 2022; 13:2743. [PMID: 35585065 PMCID: PMC9117208 DOI: 10.1038/s41467-022-30187-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 04/20/2022] [Indexed: 12/15/2022] Open
Abstract
We present the results of a GWAS of food liking conducted on 161,625 participants from the UK-Biobank. Liking was assessed over 139 specific foods using a 9-point scale. Genetic correlations coupled with structural equation modelling identified a multi-level hierarchical map of food-liking with three main dimensions: "Highly-palatable", "Acquired" and "Low-caloric". The Highly-palatable dimension is genetically uncorrelated from the other two, suggesting that independent processes underlie liking high reward foods. This is confirmed by genetic correlations with MRI brain traits which show with distinct associations. Comparison with the corresponding food consumption traits shows a high genetic correlation, while liking exhibits twice the heritability. GWAS analysis identified 1,401 significant food-liking associations which showed substantial agreement in the direction of effects with 11 independent cohorts. In conclusion, we created a comprehensive map of the genetic determinants and associated neurophysiological factors of food-liking.
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Affiliation(s)
- Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Nana Matoba
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kaitlin H Wade
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Jouke-Jan Hottenga
- Dept of Biological Psychology, FGB, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maria Pina Concas
- Institute for Maternal and Child Health-IRCCS, Burlo Garofolo, Trieste, Italy
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, UK
| | - Eryk J Grzeszkowiak
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Paolo Gasparini
- Institute for Maternal and Child Health-IRCCS, Burlo Garofolo, Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Nicholas J Timpson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Maria G Veldhuizen
- Department of Anatomy, Faculty of Medicine, Mersin University, Mersin, Turkey
| | - Eco de Geus
- Dept of Biological Psychology, FGB, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health research institute, Amsterdam, UMC, The Netherlands
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK.
- Human Technopole, Milan, Italy.
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213
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Bhat GR, Sethi I, Rah B, Kumar R, Afroze D. Innovative in Silico Approaches for Characterization of Genes and Proteins. Front Genet 2022; 13:865182. [PMID: 35664302 PMCID: PMC9159363 DOI: 10.3389/fgene.2022.865182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
Bioinformatics is an amalgamation of biology, mathematics and computer science. It is a science which gathers the information from biology in terms of molecules and applies the informatic techniques to the gathered information for understanding and organizing the data in a useful manner. With the help of bioinformatics, the experimental data generated is stored in several databases available online like nucleotide database, protein databases, GENBANK and others. The data stored in these databases is used as reference for experimental evaluation and validation. Till now several online tools have been developed to analyze the genomic, transcriptomic, proteomics, epigenomics and metabolomics data. Some of them include Human Splicing Finder (HSF), Exonic Splicing Enhancer Mutation taster, and others. A number of SNPs are observed in the non-coding, intronic regions and play a role in the regulation of genes, which may or may not directly impose an effect on the protein expression. Many mutations are thought to influence the splicing mechanism by affecting the existing splice sites or creating a new sites. To predict the effect of mutation (SNP) on splicing mechanism/signal, HSF was developed. Thus, the tool is helpful in predicting the effect of mutations on splicing signals and can provide data even for better understanding of the intronic mutations that can be further validated experimentally. Additionally, rapid advancement in proteomics have steered researchers to organize the study of protein structure, function, relationships, and dynamics in space and time. Thus the effective integration of all of these technological interventions will eventually lead to steering up of next-generation systems biology, which will provide valuable biological insights in the field of research, diagnostic, therapeutic and development of personalized medicine.
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Affiliation(s)
- Gh. Rasool Bhat
- Advanced Centre for Human Genetics, Sher-I- Kashmir Institute of Medical Sciences, Soura, India
| | - Itty Sethi
- Institute of Human Genetics, University of Jammu, Jammu, India
| | - Bilal Rah
- Advanced Centre for Human Genetics, Sher-I- Kashmir Institute of Medical Sciences, Soura, India
| | - Rakesh Kumar
- School of Biotechnology, Shri Mata Vaishno Devi University, Katra, India
| | - Dil Afroze
- Advanced Centre for Human Genetics, Sher-I- Kashmir Institute of Medical Sciences, Soura, India
- *Correspondence: Dil Afroze,
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214
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Damert A. SVA retrotransposons and a low copy repeat in humans and great apes: a mobile connection. Mol Biol Evol 2022; 39:6586216. [PMID: 35574660 PMCID: PMC9132208 DOI: 10.1093/molbev/msac103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Segmental duplications (SDs) constitute a considerable fraction of primate genomes. They contribute to genetic variation and provide raw material for evolution. Groups of SDs are characterized by the presence of shared core duplicons. One of these core duplicons, low copy repeat (lcr)16a, has been shown to be particularly active in the propagation of interspersed SDs in primates. The underlying mechanisms are, however, only partially understood. Alu short interspersed elements (SINEs) are frequently found at breakpoints and have been implicated in the expansion of SDs. Detailed analysis of lcr16a-containing SDs shows that the hominid-specific SVA (SINE-R-VNTR-Alu) retrotransposon is an integral component of the core duplicon in Asian and African great apes. In orang-utan, it provides breakpoints and contributes to both interchromosomal and intrachromosomal lcr16a mobility by inter-element recombination. Furthermore, the data suggest that in hominines (human, chimpanzee, gorilla) SVA recombination-mediated integration of a circular intermediate is the founding event of a lineage-specific lcr16a expansion. One of the hominine lcr16a copies displays large flanking direct repeats, a structural feature shared by other SDs in the human genome. Taken together, the results obtained extend the range of SVAs’ contribution to genome evolution from RNA-mediated transduction to DNA-based recombination. In addition, they provide further support for a role of circular intermediates in SD mobilization.
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Affiliation(s)
- Annette Damert
- Infection Biology Unit and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
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215
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Genetic analyses identify pleiotropy and causality for blood proteins and highlight Wnt/β-catenin signalling in migraine. Nat Commun 2022; 13:2593. [PMID: 35546551 PMCID: PMC9095680 DOI: 10.1038/s41467-022-30184-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 04/20/2022] [Indexed: 11/18/2022] Open
Abstract
Migraine is a common complex disorder with a significant polygenic SNP heritability (\documentclass[12pt]{minimal}
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\begin{document}$${h}_{{SNP}}^{2}$$\end{document}hSNP2). Here we utilise genome-wide association study (GWAS) summary statistics to study pleiotropy between blood proteins and migraine under the polygenic model. We estimate \documentclass[12pt]{minimal}
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\begin{document}$${h}_{{SNP}}^{2}$$\end{document}hSNP2 for 4625 blood protein GWASs and identify 325 unique proteins with a significant \documentclass[12pt]{minimal}
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\begin{document}$${h}_{{SNP}}^{2}$$\end{document}hSNP2 for use in subsequent genetic analyses. Pleiotropy analyses link 58 blood proteins to migraine risk at genome-wide, gene and/or single-nucleotide polymorphism levels—suggesting shared genetic influences or causal relationships. Notably, the identified proteins are largely distinct from migraine GWAS loci. We show that higher levels of DKK1 and PDGFB, and lower levels of FARS2, GSTA4 and CHIC2 proteins have a significant causal effect on migraine. The risk-increasing effect of DKK1 is particularly interesting—indicating a role for downregulation of β-catenin-dependent Wnt signalling in migraine risk, suggesting Wnt activators that restore Wnt/β-catenin signalling in brain could represent therapeutic tools against migraine. Understanding of the causes and treatment of migraine is incomplete. Here, the authors detect pleiotropic genetic effects and causal relationships between migraine and 58 proteins that are largely distinct from migraine-associated loci identified by GWAS.
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216
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Xu Y, Liu Z, Yao J. An eigenvalue ratio approach to inferring population structure from whole genome sequencing data. Biometrics 2022. [PMID: 35532153 DOI: 10.1111/biom.13691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 04/26/2022] [Indexed: 11/30/2022]
Abstract
Inference of population structure from genetic data plays an important role in population and medical genetics studies. With the advancement and decreasing cost of sequencing technology, the increasingly available whole genome sequencing data provide much richer information about the underlying population structure. The traditional method (Patterson et al., 2006) originally developed for array-based genotype data for computing and selecting top principal components that capture population structure may not perform well on sequencing data for two reasons. First, the number of genetic variants p is much larger than the sample size n in sequencing data such that the sample-to-marker ratio n/p is nearly zero, violating the assumption of the Tracy-Widom test used in their method. Second, their method might not be able to handle the linkage disequilibrium well in sequencing data. To resolve those two practical issues, we propose a new method called ERStruct to determine the number of top informative principal components based on sequencing data. More specifically, we propose to use the ratio of consecutive eigenvalues as a more robust test statistic, and then we approximate its null distribution using modern random matrix theory. Both simulation studies and applications to two public data sets from the HapMap 3 and the 1000 Genomes Projects demonstrate the empirical performance of our ERStruct method. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Yuyang Xu
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China
| | - Zhonghua Liu
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China
| | - Jianfeng Yao
- School of Data Science, The Chinese University of Hong Kong (Shenzhen), Shenzhen, China
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217
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Gakis G, Perner S, Stenzl A, Renninger M. The CAG-triplet in the androgen receptor gene and single-nucleotide polymorphisms in androgen pathway genes in patients with concomitant bladder and prostate cancer. Urol Oncol 2022; 40:198.e1-198.e8. [DOI: 10.1016/j.urolonc.2022.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/20/2022] [Accepted: 03/19/2022] [Indexed: 10/18/2022]
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218
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Kim K, Joo YY, Ahn G, Wang HH, Moon SY, Kim H, Ahn WY, Cha J. The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children. Hum Brain Mapp 2022; 43:3857-3872. [PMID: 35471639 PMCID: PMC9294341 DOI: 10.1002/hbm.25888] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/28/2022] [Accepted: 04/05/2022] [Indexed: 11/06/2022] Open
Abstract
Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9-10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC-AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (pfdr < .001, η p 2 $$ {\eta}_p^2 $$ = .011-.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (pfdr < .001, η p 2 $$ {\eta}_p^2 $$ < .005). Structural equation models revealed that the GPS-intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006-.009; p = .002-.022; sex-stratified analysis). The finding of the sex modulatory effect on the gene-brain-cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.
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Affiliation(s)
- Kakyeong Kim
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | | | - Gun Ahn
- Interdisciplinary Program of Bioengineering, College of Engineering, Seoul National University, Seoul, South Korea
| | - Hee-Hwan Wang
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | - Seo-Yoon Moon
- College of Liberal Studies, Seoul National University, Seoul, South Korea
| | - Hyeonjin Kim
- Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea
| | - Woo-Young Ahn
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea.,Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea.,AI Institute, Seoul National University, Seoul, South Korea
| | - Jiook Cha
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea.,Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea.,AI Institute, Seoul National University, Seoul, South Korea
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219
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Firoozbakht F, Rezaeian I, Rueda L, Ngom A. Computationally repurposing drugs for breast cancer subtypes using a network-based approach. BMC Bioinformatics 2022; 23:143. [PMID: 35443626 PMCID: PMC9020161 DOI: 10.1186/s12859-022-04662-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 03/30/2022] [Indexed: 11/22/2022] Open
Abstract
‘De novo’ drug discovery is costly, slow, and with high risk. Repurposing known drugs for treatment of other diseases offers a fast, low-cost/risk and highly-efficient method toward development of efficacious treatments. The emergence of large-scale heterogeneous biomolecular networks, molecular, chemical and bioactivity data, and genomic and phenotypic data of pharmacological compounds is enabling the development of new area of drug repurposing called ‘in silico’ drug repurposing, i.e., computational drug repurposing (CDR). The aim of CDR is to discover new indications for an existing drug (drug-centric) or to identify effective drugs for a disease (disease-centric). Both drug-centric and disease-centric approaches have the common challenge of either assessing the similarity or connections between drugs and diseases. However, traditional CDR is fraught with many challenges due to the underlying complex pharmacology and biology of diseases, genes, and drugs, as well as the complexity of their associations. As such, capturing highly non-linear associations among drugs, genes, diseases by most existing CDR methods has been challenging. We propose a network-based integration approach that can best capture knowledge (and complex relationships) contained within and between drugs, genes and disease data. A network-based machine learning approach is applied thereafter by using the extracted knowledge and relationships in order to identify single and pair of approved or experimental drugs with potential therapeutic effects on different breast cancer subtypes. Indeed, further clinical analysis is needed to confirm the therapeutic effects of identified drugs on each breast cancer subtype.
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Affiliation(s)
- Forough Firoozbakht
- School of Computer Science, University of Windsor, 401 Sunset Ave., Windsor, ON, Canada
| | - Iman Rezaeian
- School of Computer Science, University of Windsor, 401 Sunset Ave., Windsor, ON, Canada.,Rocket Innovation Studio, 156 Chatham St W, Windsor, ON, Canada
| | - Luis Rueda
- School of Computer Science, University of Windsor, 401 Sunset Ave., Windsor, ON, Canada.
| | - Alioune Ngom
- School of Computer Science, University of Windsor, 401 Sunset Ave., Windsor, ON, Canada
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220
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Zhao B, Li T, Smith SM, Xiong D, Wang X, Yang Y, Luo T, Zhu Z, Shan Y, Matoba N, Sun Q, Yang Y, Hauberg ME, Bendl J, Fullard JF, Roussos P, Lin W, Li Y, Stein JL, Zhu H. Common variants contribute to intrinsic human brain functional networks. Nat Genet 2022; 54:508-517. [PMID: 35393594 DOI: 10.1038/s41588-022-01039-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/28/2022] [Indexed: 01/01/2023]
Abstract
The human brain forms functional networks of correlated activity, which have been linked with both cognitive and clinical outcomes. However, the genetic variants affecting brain function are largely unknown. Here, we used resting-state functional magnetic resonance images from 47,276 individuals to discover and validate common genetic variants influencing intrinsic brain activity. We identified 45 new genetic regions associated with brain functional signatures (P < 2.8 × 10-11), including associations to the central executive, default mode, and salience networks involved in the triple-network model of psychopathology. A number of brain activity-associated loci colocalized with brain disorders (e.g., the APOE ε4 locus with Alzheimer's disease). Variation in brain function was genetically correlated with brain disorders, such as major depressive disorder and schizophrenia. Together, our study provides a step forward in understanding the genetic architecture of brain functional networks and their genetic links to brain-related complex traits and disorders.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics, Purdue University, West Lafayette, IN, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Di Xiong
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tianyou Luo
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ziliang Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Shan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nana Matoba
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yuchen Yang
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mads E Hauberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
| | - Jaroslav Bendl
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panagiotis Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Weili Lin
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Hongtu Zhu
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. .,Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. .,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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221
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Brouwer RM, Klein M, Grasby KL, Schnack HG, Jahanshad N, Teeuw J, Thomopoulos SI, Sprooten E, Franz CE, Gogtay N, Kremen WS, Panizzon MS, Olde Loohuis LM, Whelan CD, Aghajani M, Alloza C, Alnæs D, Artiges E, Ayesa-Arriola R, Barker GJ, Bastin ME, Blok E, Bøen E, Breukelaar IA, Bright JK, Buimer EEL, Bülow R, Cannon DM, Ciufolini S, Crossley NA, Damatac CG, Dazzan P, de Mol CL, de Zwarte SMC, Desrivières S, Díaz-Caneja CM, Doan NT, Dohm K, Fröhner JH, Goltermann J, Grigis A, Grotegerd D, Han LKM, Harris MA, Hartman CA, Heany SJ, Heindel W, Heslenfeld DJ, Hohmann S, Ittermann B, Jansen PR, Janssen J, Jia T, Jiang J, Jockwitz C, Karali T, Keeser D, Koevoets MGJC, Lenroot RK, Malchow B, Mandl RCW, Medel V, Meinert S, Morgan CA, Mühleisen TW, Nabulsi L, Opel N, de la Foz VOG, Overs BJ, Paillère Martinot ML, Redlich R, Marques TR, Repple J, Roberts G, Roshchupkin GV, Setiaman N, Shumskaya E, Stein F, Sudre G, Takahashi S, Thalamuthu A, Tordesillas-Gutiérrez D, van der Lugt A, van Haren NEM, Wardlaw JM, Wen W, Westeneng HJ, Wittfeld K, Zhu AH, Zugman A, Armstrong NJ, Bonfiglio G, Bralten J, Dalvie S, Davies G, Di Forti M, Ding L, Donohoe G, Forstner AJ, Gonzalez-Peñas J, Guimaraes JPOFT, Homuth G, Hottenga JJ, Knol MJ, Kwok JBJ, Le Hellard S, Mather KA, Milaneschi Y, Morris DW, Nöthen MM, Papiol S, Rietschel M, Santoro ML, Steen VM, Stein JL, Streit F, Tankard RM, Teumer A, van 't Ent D, van der Meer D, van Eijk KR, Vassos E, Vázquez-Bourgon J, Witt SH, Adams HHH, Agartz I, Ames D, Amunts K, Andreassen OA, Arango C, Banaschewski T, Baune BT, Belangero SI, Bokde ALW, Boomsma DI, Bressan RA, Brodaty H, Buitelaar JK, Cahn W, Caspers S, Cichon S, Crespo-Facorro B, Cox SR, Dannlowski U, Elvsåshagen T, Espeseth T, Falkai PG, Fisher SE, Flor H, Fullerton JM, Garavan H, Gowland PA, Grabe HJ, Hahn T, Heinz A, Hillegers M, Hoare J, Hoekstra PJ, Ikram MA, Jackowski AP, Jansen A, Jönsson EG, Kahn RS, Kircher T, Korgaonkar MS, Krug A, Lemaitre H, Malt UF, Martinot JL, McDonald C, Mitchell PB, Muetzel RL, Murray RM, Nees F, Nenadić I, Oosterlaan J, Ophoff RA, Pan PM, Penninx BWJH, Poustka L, Sachdev PS, Salum GA, Schofield PR, Schumann G, Shaw P, Sim K, Smolka MN, Stein DJ, Trollor JN, van den Berg LH, Veldink JH, Walter H, Westlye LT, Whelan R, White T, Wright MJ, Medland SE, Franke B, Thompson PM, Hulshoff Pol HE. Genetic variants associated with longitudinal changes in brain structure across the lifespan. Nat Neurosci 2022; 25:421-432. [PMID: 35383335 PMCID: PMC10040206 DOI: 10.1038/s41593-022-01042-4] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 02/28/2022] [Indexed: 02/08/2023]
Abstract
Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
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Affiliation(s)
- Rachel M Brouwer
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands.
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, The Netherlands.
| | - Marieke Klein
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Katrina L Grasby
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Hugo G Schnack
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
- Utrecht Institute of Linguistics OTS, Utrecht University, Utrecht, The Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Jalmar Teeuw
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Emma Sprooten
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Carol E Franz
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Nitin Gogtay
- American Psychiatric Association, Washington, DC, USA
| | - William S Kremen
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- VA San Diego Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Moji Aghajani
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
- Institute of Education & Child Studies, Section Forensic Family & Youth Care, Leiden University, Leiden, The Netherlands
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Dag Alnæs
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Eric Artiges
- INSERM U1299 Trajectoires Développementales en Psychiatrie, Ecole Normale Supérieure Paris-Saclay, Université Paris Saclay, Université Paris Cité, CNRS UMR 9010; Centre Borelli, Gif-sur-Yvette, France
| | - Rosa Ayesa-Arriola
- Valdecilla Biomedical Research Institute (IDIVAL), Marqués de Valdecilla University Hospital (HUMV), School of Medicine, University of Cantabria, Santander, Spain
- CIBERSAM, Biomedical Research Network on Mental Health Area, Santander, Spain
- Universidad de Cantabria, Santander, Spain
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Mark E Bastin
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Elisabet Blok
- Department of Child and Adolescent Psychiatry/Psychology, Sophia Children's Hospital, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Erlend Bøen
- Psychosomatic and CL Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Isabella A Breukelaar
- Brain Dynamics Centre, Westmead Institute for Medical Research, University of Sydney, Westmead, NSW, Australia
| | - Joanna K Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Elizabeth E L Buimer
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Dara M Cannon
- Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Simone Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Nicolas A Crossley
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Christienne G Damatac
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Casper L de Mol
- Department of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sonja M C de Zwarte
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Sylvane Desrivières
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | | | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Juliane H Fröhner
- Section of Systems Neuroscience, Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Antoine Grigis
- Université Paris-Saclay, CEA, Neurospin, Gif-sur-Yvette, France
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Laura K M Han
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Mathew A Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Catharina A Hartman
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
| | - Sarah J Heany
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Walter Heindel
- Clinic for Radiology, University Hospital Münster, Münster, Germany
| | - Dirk J Heslenfeld
- Departments of Experimental and Clinical Psychology, Amsterdam, The Netherlands
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | | | - Philip R Jansen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Sophia Children's Hospital, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Human Genetics, VUmc, Amsterdam UMC, Amsterdam, The Netherlands
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Tianye Jia
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Science and Technology for Brain-Inspired Intelligence and MoE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Temmuz Karali
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany
- NeuroImaging Core Unit Munich (NICUM), University Hospital LMU, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany
- NeuroImaging Core Unit Munich (NICUM), University Hospital LMU, Munich, Germany
- Munich Center for Neurosciences (MCN) - Brain & Mind, Planegg-Martinsried, Germany
| | - Martijn G J C Koevoets
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Rhoshel K Lenroot
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- School of Psychiatry and Behavioral Sciences, School of Medicine, University of New Mexico, Albuquerque, NM, USA
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Berend Malchow
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - René C W Mandl
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Vicente Medel
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Catherine A Morgan
- School of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand - Rangahau Roro Aotearoa, Auckland, New Zealand
| | - Thomas W Mühleisen
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Leila Nabulsi
- Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
| | - Víctor Ortiz-García de la Foz
- Valdecilla Biomedical Research Institute (IDIVAL), Marqués de Valdecilla University Hospital (HUMV), School of Medicine, University of Cantabria, Santander, Spain
- CIBERSAM, Biomedical Research Network on Mental Health Area, Santander, Spain
- Neuroimaging Unit, Technological Facilities, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
| | | | - Marie-Laure Paillère Martinot
- INSERM U1299 Trajectoires Développementales en Psychiatrie, Ecole Normale Supérieure Paris-Saclay, Université Paris Saclay, Université Paris Cité, CNRS UMR 9010; Centre Borelli, Gif-sur-Yvette, France
- APHP, Sorbonne Université, Pitie-Salpetriere Hospital, Department of Child and Adolescent Psychiatry, Paris, France
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychology, University of Halle, Halle, Germany
| | - Tiago Reis Marques
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences (LMS), Imperial College London, London, UK
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Gloria Roberts
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Gennady V Roshchupkin
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Nikita Setiaman
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Sophia Children's Hospital, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Elena Shumskaya
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Gustavo Sudre
- Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Shun Takahashi
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Diana Tordesillas-Gutiérrez
- Department of Radiology, IDIVAL, Marqués de Valdecilla University Hospital, Santander, Spain
- Advanced Computing and e-Science, Instituto de Física de Cantabria (UC-CSIC), Santander, Spain
| | - Aad van der Lugt
- Department of Radiology & Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Neeltje E M van Haren
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Sophia Children's Hospital, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Joanna M Wardlaw
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences and UK Dementia Research Institute Centre, University of Edinburgh, Edinburgh, UK
| | - Wei Wen
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Henk-Jan Westeneng
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Alyssa H Zhu
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Andre Zugman
- Laboratory of Integrative Neuroscience (LiNC), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), CNPq, São Paulo, Brazil
| | | | - Gaia Bonfiglio
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, The Netherlands
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Shareefa Dalvie
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Gail Davies
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Linda Ding
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Gary Donohoe
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Andreas J Forstner
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Centre for Human Genetics, Philipps-University Marburg, Marburg, Germany
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Javier Gonzalez-Peñas
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Joao P O F T Guimaraes
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Jouke-Jan Hottenga
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Maria J Knol
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - John B J Kwok
- Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Stephanie Le Hellard
- NORMENT Centre of Excellence, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Karen A Mather
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Sergi Papiol
- CIBERSAM, Biomedical Research Network on Mental Health Area, Santander, Spain
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital LMU, Munich, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marcos L Santoro
- Laboratory of Integrative Neuroscience (LiNC), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), CNPq, São Paulo, Brazil
- Department of Morphology and Genetics, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
| | - Vidar M Steen
- NORMENT Centre of Excellence, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Jason L Stein
- Department of Genetics & UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fabian Streit
- Department of Genetic Epidemiology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Rick M Tankard
- Mathematics and Statistics, Curtin University, Perth, WA, Australia
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Dennis van 't Ent
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Dennis van der Meer
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Kristel R van Eijk
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Javier Vázquez-Bourgon
- Valdecilla Biomedical Research Institute (IDIVAL), Marqués de Valdecilla University Hospital (HUMV), School of Medicine, University of Cantabria, Santander, Spain
- CIBERSAM, Biomedical Research Network on Mental Health Area, Santander, Spain
- Universidad de Cantabria, Santander, Spain
| | - Stephanie H Witt
- Department of Genetic Epidemiology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - Hieab H H Adams
- Department of Radiology & Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile
| | - Ingrid Agartz
- NORMENT Centre, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - David Ames
- Academic Unit for Psychiatry of Old Age, University of Melbourne, Parkville, VIC, Australia
- National Ageing Research Institute, Parkville, VIC, Australia
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Bernhard T Baune
- Department of Psychiatry, University of Melbourne, Melbourne VIC, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Sintia I Belangero
- Laboratory of Integrative Neuroscience (LiNC), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), CNPq, São Paulo, Brazil
- Department of Morphology and Genetics, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
| | - Arun L W Bokde
- Discipline of Psychiatry and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Rodrigo A Bressan
- Laboratory of Integrative Neuroscience (LiNC), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), CNPq, São Paulo, Brazil
- Instituto Ame Sua Mente, São Paulo, Brazil
| | - Henry Brodaty
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
- Altrecht Science, Altrecht Mental Health Institute, Utrecht, The Netherlands
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Sven Cichon
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Department of Biomedicine, University of Basel, Basel, Switzerland
- Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Benedicto Crespo-Facorro
- CIBERSAM, Biomedical Research Network on Mental Health Area, Santander, Spain
- Department of Psychiatry, Virgen del Rocio University Hospital, School of Medicine, University of Seville, IBIS, Seville, Spain
| | - Simon R Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Torbjørn Elvsåshagen
- NORMENT Centre, Oslo University Hospital, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Thomas Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway
- Bjørknes College, Oslo, Norway
| | - Peter G Falkai
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany
| | - Simon E Fisher
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Janice M Fullerton
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Penny A Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Hans J Grabe
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | | | - Manon Hillegers
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Sophia Children's Hospital, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jacqueline Hoare
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- Faculty of Health, Peninsula Medical School, University of Plymouth, Plymouth, UK
| | - Pieter J Hoekstra
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry & Accare Child Study Center, Groningen, The Netherlands
| | - Mohammad A Ikram
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Andrea P Jackowski
- Laboratory of Integrative Neuroscience (LiNC), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), CNPq, São Paulo, Brazil
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Erik G Jönsson
- NORMENT Centre, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Rene S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- VISN 2 Mental Illness Research, Education & Clinical Center (MIRECC), James J. Peters Department of Veterans Affairs Medical Center, Bronx, NY, USA
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, Westmead Institute for Medical Research, University of Sydney, Westmead, NSW, Australia
- Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Herve Lemaitre
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, CNRS UMR 5293, Université de Bordeaux, Centre Broca Nouvelle-Aquitaine, Bordeaux, France
| | - Ulrik F Malt
- Unit for Psychosomatic Medicine and C-L Psychiatry, University of Oslo, Oslo, Norway
| | - Jean-Luc Martinot
- INSERM U1299 Trajectoires Développementales en Psychiatrie, Ecole Normale Supérieure Paris-Saclay, Université Paris Saclay, Université Paris Cité, CNRS UMR 9010; Centre Borelli, Gif-sur-Yvette, France
| | - Colm McDonald
- Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Philip B Mitchell
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Sophia Children's Hospital, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Jaap Oosterlaan
- Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Emma Neuroscience Group, Department of Pediatrics, Amsterdam Reproduction & Development, Amsterdam, The Netherlands
- Vrije Universiteit, Clinical Neuropsychology Section, Amsterdam, The Netherlands
| | - Roel A Ophoff
- Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Erasmus Medical Center, Erasmus University, Rotterdam, The Netherlands
| | - Pedro M Pan
- Laboratory of Integrative Neuroscience (LiNC), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), CNPq, São Paulo, Brazil
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry, University Medical Center Goettingen, Göttingen, Germany
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, Sydney, NSW, Australia
| | - Giovanni A Salum
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), CNPq, São Paulo, Brazil
- Department of Psychiatry and Legal Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Gunter Schumann
- Center for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
- PONS Centre, Department of Psychiatry and Clinical Neuroscience, CCM, Charite University Medicine, Berlin, Germany
| | - Philip Shaw
- Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Julian N Trollor
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
- Department of Developmental Disability Neuropsychiatry, Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Leonard H van den Berg
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Jan H Veldink
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Henrik Walter
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute for Health, Berlin, Germany
| | - Lars T Westlye
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Robert Whelan
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Tonya White
- Department of Child and Adolescent Psychiatry/Psychology, Sophia Children's Hospital, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands.
- Department of Psychology, Utrecht University, Utrecht, The Netherlands.
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Kim R, An M, Lee H, Mehta A, Heo YJ, Kim KM, Lee SY, Moon J, Kim ST, Min BH, Kim TJ, Rha SY, Kang WK, Park WY, Klempner SJ, Lee J. Early Tumor-Immune Microenvironmental Remodeling and Response to First-Line Fluoropyrimidine and Platinum Chemotherapy in Advanced Gastric Cancer. Cancer Discov 2022; 12:984-1001. [PMID: 34933901 PMCID: PMC9387589 DOI: 10.1158/2159-8290.cd-21-0888] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 10/17/2021] [Accepted: 12/16/2021] [Indexed: 01/07/2023]
Abstract
Chemotherapy is ubiquitous in first-line treatment of advanced gastric cancer, yet responses are heterogeneous, and little is known about mediators of chemotherapy response. To move forward, an understanding of the effects of standard chemotherapy on the tumor-immune microenvironment (TME) is needed. Coupling whole-exome sequencing, bulk RNA and single-cell transcriptomics from paired pretreatment and on-treatment samples in treatment-naïve patients with HER2-positive and HER2-negative gastric cancer, we define features associated with response to platinum-based chemotherapy. Response was associated with on-treatment TME remodeling including natural killer (NK) cell recruitment, decreased tumor-associated macrophages, M1-macrophage repolarization, and increased effector T-cell infiltration. Among chemotherapy nonresponders, we observed low/absent PD-L1 expression or modulation, on-treatment increases in Wnt signaling, B-cell infiltration, and LAG3-expressing T cells coupled to an exodus of dendritic cells. We did not observe significant genomic changes in early on-treatment sampling. We provide a map of on-treatment TME modulation with standard chemotherapy and nominate candidate future approaches. SIGNIFICANCE Using paired pretreatment and on-treatment samples during standard first-line chemotherapy, we identify chemotherapy-induced NK-cell infiltration, macrophage repolarization, and increased antigen presentation among responders. Increased LAG3 expression and decreased dendritic cell abundance were seen in nonresponders, emphasizing remodeling of the TME during chemotherapy response and resistance. This article is highlighted in the In This Issue feature, p. 873.
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Affiliation(s)
- Ryul Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Minae An
- Samsung Advanced Institute of Health Science and Technology, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hyuk Lee
- Department of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Arnav Mehta
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Division of Hematology-Oncology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | - You Jeong Heo
- Samsung Advanced Institute of Health Science and Technology, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Kyoung-Mee Kim
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Song-Yi Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | | | - Seung Tae Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Byung-Hoon Min
- Department of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Tae Jun Kim
- Department of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sun Young Rha
- Department of Medical Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea
| | - Won Ki Kang
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Woong-Yang Park
- Geninus Inc., Seoul, Korea
- Samsung Genome Institute, Samsung Medical Center, Seoul, Korea
- Corresponding Authors: Samuel J. Klempner, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114. Phone: 617-724-4000; Fax: 617-726-0452; E-mail: ; Woong-Yang Park, Department of Health Sciences and Technology, SAIHST, Samsung Medical Center Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea. Phone: 82-2-2148-9810; Fax: 82-2-2148-9819; E-mail: ; and Jeeyun Lee, Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea. Phone: 82-2-3410-1779; Fax: 82-2-3410-1754; E-mail:
| | - Samuel J. Klempner
- Division of Hematology-Oncology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Corresponding Authors: Samuel J. Klempner, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114. Phone: 617-724-4000; Fax: 617-726-0452; E-mail: ; Woong-Yang Park, Department of Health Sciences and Technology, SAIHST, Samsung Medical Center Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea. Phone: 82-2-2148-9810; Fax: 82-2-2148-9819; E-mail: ; and Jeeyun Lee, Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea. Phone: 82-2-3410-1779; Fax: 82-2-3410-1754; E-mail:
| | - Jeeyun Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
- Corresponding Authors: Samuel J. Klempner, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114. Phone: 617-724-4000; Fax: 617-726-0452; E-mail: ; Woong-Yang Park, Department of Health Sciences and Technology, SAIHST, Samsung Medical Center Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea. Phone: 82-2-2148-9810; Fax: 82-2-2148-9819; E-mail: ; and Jeeyun Lee, Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea. Phone: 82-2-3410-1779; Fax: 82-2-3410-1754; E-mail:
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Song W, Lin GN, Yu S, Zhao M. Genome-wide identification of the shared genetic basis of cannabis and cigarette smoking and schizophrenia implicates NCAM1 and neuronal abnormality. Psychiatry Res 2022; 310:114453. [PMID: 35235886 DOI: 10.1016/j.psychres.2022.114453] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/31/2022] [Accepted: 02/15/2022] [Indexed: 01/02/2023]
Abstract
OBJECTIVES Confirming the existence and composition of the shared genetic basis of Schizophrenia and cannabis and cigarette smoking has critical values for the clinical prevention and intervention of psychosis. METHODS To achieve this goal, we leveraged Genome-Wide summary statistics of Schizophrenia (n = 99,934), cigarette smoking (n = 518,633) and cannabis usage (n = 162,082). We applied Causal Analysis Using Summary Effect Estimates (CAUSE) and genomic structural equation modeling (GenomicSEM) to quantify the contribution of a common genetic factor of cannabis and cigarette smoking and schizophrenia (referred to as SCZ_SMO), then identified genome-wide loci that made up SCZ_SMO. RESULTS We estimated that SCZ_SMO explained 8.6% of Schizophrenia heritability (Z score <-2.5 in CAUSE, p<10-20 in Genomic SEM). There were 20 independent loci showing association with SCZ_SMO at the genome-wide threshold of p<5 × 10-8. At the top locus on chromosome 11, fine-mapping identified rs7945073 (posterior inclusion probability =0.12, p = 2.24 × 10-32) as the top risk variants. Gene-level association and fine-mapping highlighted NCAM1, PHC2, and SEMA6D as risk genes of SCZ_SMO. Other risk genes were enriched in cortex, neuron, and dendritic spines (adjusted p<0.05). SCZ_SMO showed significant positive correlation (p<10-6) with the genetic risk of attention deficit hyperactivity disorder (r = 0.50), lifestyle problems (r = 0.83), social deprivation (r = 0.58) and all-cause pregnant loss (r = 0.60). CONCLUSION Our result provided new evidence on the shared genetic basis model for the association between Schizophrenia and smoking and provided genetic and biological insights into their shared mechanism.
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Affiliation(s)
- Weichen Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Guan Ning Lin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Shunying Yu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Min Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences, Shanghai, China.
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Epigenome-Wide Analysis Reveals DNA Methylation Alteration in ZFP57 and Its Target RASGFR2 in a Mexican Population Cohort with Autism. CHILDREN (BASEL, SWITZERLAND) 2022; 9:children9040462. [PMID: 35455506 PMCID: PMC9025761 DOI: 10.3390/children9040462] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/18/2022] [Accepted: 03/20/2022] [Indexed: 12/17/2022]
Abstract
Autism Spectrum Disorders (ASD) comprise a group of heterogeneous and complex neurodevelopmental disorders. Genetic and environmental factors contribute to ASD etiology. DNA methylation is particularly relevant for ASD due to its mediating role in the complex interaction between genotype and environment and has been implicated in ASD pathophysiology. The lack of diversity in DNA methylation studies in ASD individuals is remarkable. Since genetic and environmental factors are likely to vary across populations, the study of underrepresented populations is necessary to understand the molecular alterations involved in ASD and the risk factors underlying these changes. This study explored genome-wide differences in DNA methylation patterns in buccal epithelium cells between Mexican ASD patients (n = 27) and age-matched typically developing (TD: n = 15) children. DNA methylation profiles were evaluated with the Illumina 450k array. We evaluated the interaction between sex and ASD and found a differentially methylated region (DMR) over the 5′UTR region of ZFP57 and one of its targets, RASGRF2. These results match previous findings in brain tissue, which may indicate that ZFP57 could be used as a proxy for DNA methylation in different tissues. This is the first study performed in a Mexican, and subsequently, Latin American, population that evaluates DNA methylation in ASD patients.
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225
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Prince C, Sharp GC, Howe LD, Fraser A, Richmond RC. The relationships between women's reproductive factors: a Mendelian randomisation analysis. BMC Med 2022; 20:103. [PMID: 35321746 PMCID: PMC8944090 DOI: 10.1186/s12916-022-02293-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 02/09/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Women's reproductive factors include their age at menarche and menopause, the age at which they start and stop having children and the number of children they have. Studies that have linked these factors with disease risk have largely investigated individual reproductive factors and have not considered the genetic correlation and total interplay that may occur between them. This study aimed to investigate the nature of the relationships between eight female reproductive factors. METHODS We used data from the UK Biobank and genetic consortia with data available for the following reproductive factors: age at menarche, age at menopause, age at first birth, age at last birth, number of births, being parous, age first had sexual intercourse and lifetime number of sexual partners. Linkage disequilibrium score regression (LDSC) was performed to investigate the genetic correlation between reproductive factors. We then applied Mendelian randomisation (MR) methods to estimate the causal relationships between these factors. Sensitivity analyses were used to investigate directionality of the effects, test for evidence of pleiotropy and account for sample overlap. RESULTS LDSC indicated that most reproductive factors are genetically correlated (rg range: |0.06-0.94|), though there was little evidence for genetic correlations between lifetime number of sexual partners and age at last birth, number of births and ever being parous (rg < 0.01). MR revealed potential causal relationships between many reproductive factors, including later age at menarche (1 SD increase) leading to a later age at first sexual intercourse (beta (B) = 0.09 SD, 95% confidence intervals (CI) = 0.06,0.11), age at first birth (B = 0.07 SD, CI = 0.04,0.10), age at last birth (B = 0.06 SD, CI = 0.04,0.09) and age at menopause (B = 0.06 SD, CI = 0.03,0.10). Later age at first birth was found to lead to a later age at menopause (B = 0.21 SD, CI = 0.13,0.29), age at last birth (B = 0.72 SD, CI = 0.67, 0.77) and a lower number of births (B = -0.38 SD, CI = -0.44, -0.32). CONCLUSION This study presents evidence that women's reproductive factors are genetically correlated and causally related. Future studies examining the health sequelae of reproductive factors should consider a woman's entire reproductive history, including the causal interplay between reproductive factors.
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Affiliation(s)
- Claire Prince
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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226
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Genetic mosaicism in the human brain: from lineage tracing to neuropsychiatric disorders. Nat Rev Neurosci 2022; 23:275-286. [PMID: 35322263 DOI: 10.1038/s41583-022-00572-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/11/2022] [Indexed: 12/18/2022]
Abstract
Genetic mosaicism is the result of the accumulation of somatic mutations in the human genome starting from the first postzygotic cell generation and continuing throughout the whole life of an individual. The rapid development of next-generation and single-cell sequencing technologies is now allowing the study of genetic mosaicism in normal tissues, revealing unprecedented insights into their clonal architecture and physiology. The somatic variant repertoire of an adult human neuron is the result of somatic mutations that accumulate in the brain by different mechanisms and at different rates during development and ageing. Non-pathogenic developmental mutations function as natural barcodes that once identified in deep bulk or single-cell sequencing can be used to retrospectively reconstruct human lineages. This approach has revealed novel insights into the clonal structure of the human brain, which is a mosaic of clones traceable to the early embryo that contribute differentially to the brain and distinct areas of the cortex. Some of the mutations happening during development, however, have a pathogenic effect and can contribute to some epileptic malformations of cortical development and autism spectrum disorder. In this Review, we discuss recent findings in the context of genetic mosaicism and their implications for brain development and disease.
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227
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Yang L, Gao Y, Oswalt A, Fang L, Boschiero C, Neupane M, Sattler CG, Li CJ, Seroussi E, Xu L, Yang L, Li L, Zhang H, Rosen BD, Van Tassell CP, Zhou Y, Ma L, Liu GE. Towards the detection of copy number variation from single sperm sequencing in cattle. BMC Genomics 2022; 23:215. [PMID: 35300589 PMCID: PMC8928590 DOI: 10.1186/s12864-022-08441-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 10/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Copy number variation (CNV) has been routinely studied using bulk-cell sequencing. However, CNV is not well studied on the single-cell level except for humans and a few model organisms. RESULTS We sequenced 143 single sperms of two Holstein bulls, from which we predicted CNV events using 14 single sperms with deep sequencing. We then compared the CNV results derived from single sperms with the bulk-cell sequencing of one bull's family trio of diploid genomes. As a known CNV hotspot, segmental duplications were also predicted using the bovine ARS-UCD1.2 genome. Although the trio CNVs validated only some single sperm CNVs, they still showed a distal chromosomal distribution pattern and significant associations with segmental duplications and satellite repeats. CONCLUSION Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for CNV detection using single cell sequencing data.
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Affiliation(s)
- Liu Yang
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.,College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.,Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Adam Oswalt
- Select Sires Inc, 11740 U.S. 42 North, Plain City, OH, 43064, USA
| | - Lingzhao Fang
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Mahesh Neupane
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | | | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Eyal Seroussi
- Agricultural Research Organization (ARO), Institute of Animal Science, HaMaccabim Road, P.O.B 15159, 7528809, Volcani CenterRishon LeTsiyon, Israel
| | - Lingyang Xu
- Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Lv Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Li Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Hongping Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
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228
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Schaschl H, Göllner T, Morris DL. Positive selection acts on regulatory genetic variants in populations of European ancestry that affect ALDH2 gene expression. Sci Rep 2022; 12:4563. [PMID: 35296751 PMCID: PMC8927298 DOI: 10.1038/s41598-022-08588-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 03/09/2022] [Indexed: 11/09/2022] Open
Abstract
ALDH2 is a key enzyme in alcohol metabolism that protects cells from acetaldehyde toxicity. Using iHS, iSAFE and FST statistics, we identified regulatory acting variants affecting ALDH2 gene expression under positive selection in populations of European ancestry. Several SNPs (rs3184504, rs4766578, rs10774625, rs597808, rs653178, rs847892, rs2013002) that function as eQTLs for ALDH2 in various tissues showed evidence of strong positive selection. Very large pairwise FST values indicated high genetic differentiation at these loci between populations of European ancestry and populations of other global ancestries. Estimating the timing of positive selection on the beneficial alleles suggests that these variants were recently adapted approximately 3000-3700 years ago. The derived beneficial alleles are in complete linkage disequilibrium with the derived ALDH2 promoter variant rs886205, which is associated with higher transcriptional activity. The SNPs rs4766578 and rs847892 are located in binding sequences for the transcription factor HNF4A, which is an important regulatory element of ALDH2 gene expression. In contrast to the missense variant ALDH2 rs671 (ALDH2*2), which is common only in East Asian populations and is associated with greatly reduced enzyme activity and alcohol intolerance, the beneficial alleles of the regulatory variants identified in this study are associated with increased expression of ALDH2. This suggests adaptation of Europeans to higher alcohol consumption.
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Affiliation(s)
- Helmut Schaschl
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria.
| | - Tobias Göllner
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria
| | - David L Morris
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, Great Maze Pond, London, SE1 9RT, UK
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229
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Gakis G, Perner S, Stenzl A, Renninger M. The role of single-nucleotide polymorphisms of the 8q24 chromosome region in patients with concomitant bladder and prostate cancer. Scand J Urol 2022; 56:126-130. [PMID: 35274594 DOI: 10.1080/21681805.2022.2049362] [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: 10/18/2022]
Abstract
OBJECTIVE To assess whether single-nucleotide polymorphisms (SNPs) of the 8q24 chromosome region are associated with recurrence-free survival (RFS) after radical cystoprostatectomy (RC) in patients with concomitant bladder (BC) and prostate cancer (PC). MATERIALS AND METHODS A cohort of thirty-six patients treated with RC and pelvic lymph node dissection and histologically exhibited invasive BC and incidental PC. Using Sanger sequencing, a total of seven SNPs in the androgen-responsive element of the promoter region of the following genes were assessed in tumor-free lymph nodes and correlated with oncological outcomes: PSCA (rs2294008, rs2978974, rs1045531, rs3736001), MYC (rs6983267), FXBO32 (rs7830622), and MIR151A (rs14974929). The median follow-up was 26 months (range: 4-68). RESULTS In a dominant model, patients exhibiting rs2978974 as a minor allelic variant of the PSCA gene had worse RFS (32 vs. 75%, p = 0.015). No associations were found for the other SNPs. CONCLUSIONS These data suggest that the rs2978974 of the PSCA gene correlates with inferior BC-specific RFS after RC and should be further evaluated in larger studies.
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Affiliation(s)
- Georgios Gakis
- Department of Urology and Pediatric Urology, University Hospital of Würzburg, Julius-Maximillians University, Würzburg, Germany
| | - Sven Perner
- Institute of Pathology, University of Luebeck, University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany.,Department of Pathology, Research Center Borstel, Leibniz Lung Center, Borstel, Germany
| | - Arnulf Stenzl
- Department of Urology, University Hospital, Eberhard-Karls University, Tübingen, Germany
| | - Markus Renninger
- Department of Urology, University Hospital, Eberhard-Karls University, Tübingen, Germany
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230
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Elliott KS, Haber M, Daggag H, Busby GB, Sarwar R, Kennet D, Petraglia M, Petherbridge LJ, Yavari P, Heard-Bey FU, Shobi B, Ghulam T, Haj D, Al Tikriti A, Mohammad A, Antony S, Alyileili M, Alaydaroos S, Lau E, Butler M, Yavari A, Knight JC, Ashrafian H, Barakat MT. Fine-Scale Genetic Structure in the United Arab Emirates Reflects Endogamous and Consanguineous Culture, Population History, and Geography. Mol Biol Evol 2022; 39:msac039. [PMID: 35192718 PMCID: PMC8911814 DOI: 10.1093/molbev/msac039] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The indigenous population of the United Arab Emirates (UAE) has a unique demographic and cultural history. Its tradition of endogamy and consanguinity is expected to produce genetic homogeneity and partitioning of gene pools while population movements and intercontinental trade are likely to have contributed to genetic diversity. Emiratis and neighboring populations of the Middle East have been underrepresented in the population genetics literature with few studies covering the broader genetic history of the Arabian Peninsula. Here, we genotyped 1,198 individuals from the seven Emirates using 1.7 million markers and by employing haplotype-based algorithms and admixture analyses, we reveal the fine-scale genetic structure of the Emirati population. Shared ancestry and gene flow with neighboring populations display their unique geographic position while increased intra- versus inter-Emirati kinship and sharing of uniparental haplogroups, reflect the endogamous and consanguineous cultural traditions of the Emirates and their tribes.
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Affiliation(s)
- Katherine S Elliott
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Marc Haber
- Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom
| | - Hinda Daggag
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | - George B Busby
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Rizwan Sarwar
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Derek Kennet
- Department of Archaeology, Durham University, Durham, United Kingdom
| | - Michael Petraglia
- Max Planck Institute for the Science of Human History, Jena, Germany
| | | | - Parisa Yavari
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Bindu Shobi
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | - Tariq Ghulam
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | - Dalia Haj
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | | | | | - Suma Antony
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | | | | | - Evelyn Lau
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Mark Butler
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Arash Yavari
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Julian C Knight
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Houman Ashrafian
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
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231
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Pasman JA, Demange PA, Guloksuz S, Willemsen AHM, Abdellaoui A, Ten Have M, Hottenga JJ, Boomsma DI, de Geus E, Bartels M, de Graaf R, Verweij KJH, Smit DJ, Nivard M, Vink JM. Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status. Behav Genet 2022; 52:92-107. [PMID: 34855049 PMCID: PMC8860781 DOI: 10.1007/s10519-021-10094-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 11/10/2021] [Indexed: 11/15/2022]
Abstract
This study aims to disentangle the contribution of genetic liability, educational attainment (EA), and their overlap and interaction in lifetime smoking. We conducted genome-wide association studies (GWASs) in UK Biobank (N = 394,718) to (i) capture variants for lifetime smoking, (ii) variants for EA, and (iii) variants that contribute to lifetime smoking independently from EA ('smoking-without-EA'). Based on the GWASs, three polygenic scores (PGSs) were created for individuals from the Netherlands Twin Register (NTR, N = 17,805) and the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2, N = 3090). We tested gene-environment (G × E) interactions between each PGS, neighborhood socioeconomic status (SES) and EA on lifetime smoking. To assess if the PGS effects were specific to smoking or had broader implications, we repeated the analyses with measures of mental health. After subtracting EA effects from the smoking GWAS, the SNP-based heritability decreased from 9.2 to 7.2%. The genetic correlation between smoking and SES characteristics was reduced, whereas overlap with smoking traits was less affected by subtracting EA. The PGSs for smoking, EA, and smoking-without-EA all predicted smoking. For mental health, only the PGS for EA was a reliable predictor. There were suggestions for G × E for some relationships, but there were no clear patterns per PGS type. This study showed that the genetic architecture of smoking has an EA component in addition to other, possibly more direct components. PGSs based on EA and smoking-without-EA had distinct predictive profiles. This study shows how disentangling different models of genetic liability and interplay can contribute to our understanding of the etiology of smoking.
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Affiliation(s)
- Joëlle A Pasman
- Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, PO Box 281, 171 77, Stockholm, Sweden.
| | - Perline A Demange
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - A H M Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Margreet Ten Have
- Trimbos-Instituut, Netherlands Institute of Mental Health and Addiction, Utrecht, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ron de Graaf
- Trimbos-Instituut, Netherlands Institute of Mental Health and Addiction, Utrecht, The Netherlands
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Dirk J Smit
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Michel Nivard
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands
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232
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Pardiñas AF, Smart SE, Willcocks IR, Holmans PA, Dennison CA, Lynham AJ, Legge SE, Baune BT, Bigdeli TB, Cairns MJ, Corvin A, Fanous AH, Frank J, Kelly B, McQuillin A, Melle I, Mortensen PB, Mowry BJ, Pato CN, Periyasamy S, Rietschel M, Rujescu D, Simonsen C, St Clair D, Tooney P, Wu JQ, Andreassen OA, Kowalec K, Sullivan PF, Murray RM, Owen MJ, MacCabe JH, O’Donovan MC, Walters JTR, Ajnakina O, Alameda L, Barnes TRE, Berardi D, Bonora E, Camporesi S, Cleusix M, Conus P, Crespo-Facorro B, D'Andrea G, Demjaha A, Do KQ, Doody GA, Eap CB, Ferchiou A, Di Forti M, Guidi L, Homman L, Jenni R, Joyce EM, Kassoumeri L, Khadimallah I, Lastrina O, Muratori R, Noyan H, O'Neill FA, Pignon B, Restellini R, Richard JR, Schürhoff F, Španiel F, Szöke A, Tarricone I, Tortelli A, Üçok A, Vázquez-Bourgon J. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia. JAMA Psychiatry 2022; 79:260-269. [PMID: 35019943 PMCID: PMC8756361 DOI: 10.1001/jamapsychiatry.2021.3799] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
IMPORTANCE About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. OBJECTIVE To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. DESIGN, SETTING, AND PARTICIPANTS Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). MAIN OUTCOMES AND MEASURES GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. RESULTS The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04). CONCLUSIONS AND RELEVANCE In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.
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Affiliation(s)
- Antonio F. Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Sophie E. Smart
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom,Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Isabella R. Willcocks
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Peter A. Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Charlotte A. Dennison
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Amy J. Lynham
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Sophie E. Legge
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Bernhard T. Baune
- Department of Psychiatry, University of Münster, Münster, Germany,Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia,The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Tim B. Bigdeli
- Department of Psychiatry and the Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn,Institute for Genomic Health, State University of New York Downstate Medical Center, Brooklyn,Department of Psychiatry, Veterans Affairs New York Harbor Healthcare System, Brooklyn
| | - Murray J. Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia,Centre for Brain and Mental Health Research, University of Newcastle, Newcastle, Australia,Hunter Medical Research Institute, Newcastle, Australia
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Ayman H. Fanous
- Department of Psychiatry and the Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn,Institute for Genomic Health, State University of New York Downstate Medical Center, Brooklyn
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Mannheim, Germany
| | - Brian Kelly
- School of Medicine & Public Health, The University of Newcastle, Newcastle, Australia
| | - Andrew McQuillin
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, United Kingdom
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, Oslo, Norway
| | - Preben B. Mortensen
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Bryan J. Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia,Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, Australia
| | - Carlos N. Pato
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn,Department of Psychiatry and Zilkha Neurogenetics Institute, Keck School of Medicine, University of Southern California, Los Angeles,Institute for Genomic Health, State University of New York Downstate Medical Center, Brooklyn
| | - Sathish Periyasamy
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia,Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, Australia
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Mannheim, Germany
| | - Dan Rujescu
- University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Martin Luther University of Halle-Wittenberg, Halle, Germany,Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Carmen Simonsen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Early Intervention in Psychosis Advisory Unit for South-East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - David St Clair
- Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Paul Tooney
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia,Hunter Medical Research Institute, Newcastle, Australia
| | - Jing Qin Wu
- Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, Oslo, Norway
| | - Kaarina Kowalec
- College of Pharmacy, University of Manitoba, Winnipeg, Manitoba, Canada,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrick F. Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Department of Psychiatry, Icahn School of Medicine, Mount Sinai Hospital, New York, New York,Department of Genetics, University of North Carolina, Chapel Hill
| | - Robin M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Michael J. Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James H. MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Michael C. O’Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James T. R. Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | | | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, University of London, London, United Kingdom.,Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Luis Alameda
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.,Centro de Investigacion Biomedica en Red de Salud Mental, Spanish Network for Research in Mental Health, Sevilla, Spain.,Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio, Departamento de Psiquiatria, Universidad de Sevilla, Sevilla, Spain.,Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Thomas R E Barnes
- Division of Psychiatry, Imperial College London, London, United Kingdom
| | - Domenico Berardi
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Elena Bonora
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Sara Camporesi
- Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland.,Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Martine Cleusix
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Philippe Conus
- Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Benedicto Crespo-Facorro
- Centro de Investigacion Biomedica en Red de Salud Mental, Spanish Network for Research in Mental Health, Sevilla, Spain.,Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio, Departamento de Psiquiatria, Universidad de Sevilla, Sevilla, Spain
| | - Giuseppe D'Andrea
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Kim Q Do
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Gillian A Doody
- Department of Medical Education, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, United Kingdom
| | - Chin B Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Aziz Ferchiou
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France
| | - Marta Di Forti
- Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley National Health Service Mental Health Foundation Trust, London, United Kingdom
| | - Lorenzo Guidi
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Lina Homman
- Department of Social and Welfare Studies, Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden.,Centre For Public Health, Institute Of Clinical Sciences, Queens University Belfast, Belfast, United Kingdom
| | - Raoul Jenni
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Eileen M Joyce
- UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Laura Kassoumeri
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Inès Khadimallah
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Ornella Lastrina
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Roberto Muratori
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Handan Noyan
- Faculty of Social Sciences, Department of Psychology, Beykoz University, Istanbul, Turkey
| | - Francis A O'Neill
- Centre For Public Health, Institute Of Clinical Sciences, Queens University Belfast, Belfast, United Kingdom
| | - Baptiste Pignon
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires HMondor, Département Médico-Universitaire de Psychiatrie et d'Addictologie, Fédération Hospitalo-Universitaire de Médecine de Précision, Créteil, France
| | - Romeo Restellini
- Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland.,Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Jean-Romain Richard
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France
| | - Franck Schürhoff
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires HMondor, Département Médico-Universitaire de Psychiatrie et d'Addictologie, Fédération Hospitalo-Universitaire de Médecine de Précision, Créteil, France
| | - Filip Španiel
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Andrei Szöke
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires HMondor, Département Médico-Universitaire de Psychiatrie et d'Addictologie, Fédération Hospitalo-Universitaire de Médecine de Précision, Créteil, France
| | - Ilaria Tarricone
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Andrea Tortelli
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Groupe Hospitalier Universitaire Psychiatrie Neurosciences Paris, Pôle Psychiatrie Précarité, Paris, France
| | - Alp Üçok
- Department of Psychiatry, Istanbul University, Istanbul, Turkey
| | - Javier Vázquez-Bourgon
- Department of Psychiatry, University Hospital Marques de Valdecilla-Instituto de Investigación Marques de Valdecilla, Santander, Spain.,Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander, Spain.,Centro de Investigacion Biomedica en Red de Salud Mental, Spanish Network for Research in Mental Health, Santander, Spain
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233
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Wainschtein P, Jain D, Zheng Z, Cupples LA, Shadyab AH, McKnight B, Shoemaker BM, Mitchell BD, Psaty BM, Kooperberg C, Liu CT, Albert CM, Roden D, Chasman DI, Darbar D, Lloyd-Jones DM, Arnett DK, Regan EA, Boerwinkle E, Rotter JI, O'Connell JR, Yanek LR, de Andrade M, Allison MA, McDonald MLN, Chung MK, Fornage M, Chami N, Smith NL, Ellinor PT, Vasan RS, Mathias RA, Loos RJF, Rich SS, Lubitz SA, Heckbert SR, Redline S, Guo X, Chen YDI, Laurie CA, Hernandez RD, McGarvey ST, Goddard ME, Laurie CC, North KE, Lange LA, Weir BS, Yengo L, Yang J, Visscher PM. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. Nat Genet 2022; 54:263-273. [PMID: 35256806 PMCID: PMC9119698 DOI: 10.1038/s41588-021-00997-7] [Citation(s) in RCA: 122] [Impact Index Per Article: 61.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 12/01/2021] [Indexed: 12/20/2022]
Abstract
Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.
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Affiliation(s)
- Pierrick Wainschtein
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Aladdin H Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Barbara McKnight
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Benjamin M Shoemaker
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Christine M Albert
- Harvard Medical School, Boston, MA, USA
- Division of Cardiovascular, Brigham and Women's Hospital, Boston, MA, USA
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dan Roden
- Departments of Medicine, Pharmacology and Bioinformatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dawood Darbar
- Department of Medicine, University of Illinois-Chicago, Chicago, IL, USA
| | | | - Donna K Arnett
- Dean's Office, College of Public Health, University of Kentucky, Lexington, KY, USA
| | | | - Eric Boerwinkle
- Health Science Center, University of Texas, Houston, TX, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Mariza de Andrade
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Matthew A Allison
- Department of Family Medicine, University of California San Diego, La Jolla, CA, USA
| | - Merry-Lynn N McDonald
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mina K Chung
- Department of Molecular Cardiology, Cleveland Clinic, Cleveland, OH, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nathalie Chami
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Institute for Child Health and Development, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nicholas L Smith
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
| | - Patrick T Ellinor
- Harvard Medical School, Boston, MA, USA
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, USA
| | - Ramachandran S Vasan
- Framingham Heart Study, Framingham, MA, USA
- Sections of Preventive Medicine and Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Divisions of Allergy and Clinical Immunology and General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Institute for Child Health and Development, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Steven A Lubitz
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Susan R Heckbert
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Y -D Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Ryan D Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Stephen T McGarvey
- International Health Institute, Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
| | - Michael E Goddard
- Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
- Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kari E North
- Department of Epidemiology and Carolina Center of Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Leslie A Lange
- Department of Medicine, University of Colorado, Aurora, CO, USA
| | - Bruce S Weir
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.
- School of Life Sciences, Westlake University, Hangzhou Zhejiang, China.
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia.
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234
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Testori A, Vaksman Z, Diskin SJ, Hakonarson H, Capasso M, Iolascon A, Maris JM, Devoto M. Genetic analysis in African American children supports ancestry specific neuroblastoma susceptibility. Cancer Epidemiol Biomarkers Prev 2022; 31:870-875. [DOI: 10.1158/1055-9965.epi-21-0782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 09/15/2021] [Accepted: 01/27/2022] [Indexed: 11/16/2022] Open
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235
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Deakin CT, Bowes J, Rider LG, Miller FW, Pachman LM, Sanner H, Rouster-Stevens K, Mamyrova G, Curiel R, Feldman BM, Huber AM, Reed AM, Schmeling H, Cook CG, Marshall LR, Wilkinson MGL, Eyre S, Raychaudhuri S, Wedderburn LR. Association with HLA-DRβ1 position 37 distinguishes juvenile Dermatomyositis from adult-onset myositis. Hum Mol Genet 2022; 31:2471-2481. [PMID: 35094092 PMCID: PMC9307311 DOI: 10.1093/hmg/ddac019] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 01/14/2022] [Accepted: 01/17/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
Objectives
Juvenile dermatomyositis (JDM) is a rare, severe autoimmune disease and the most common idiopathic inflammatory myopathy (IIM) of children. JDM and adult-onset dermatomyositis (DM) have similar clinical, biological and serological features, although these features differ in prevalence between childhood-onset and adult-onset disease, suggesting age of disease onset may influence pathogenesis. Therefore, a JDM-focused genetic analysis was performed using the largest collection of JDM samples to date.
Methods
Caucasian JDM samples (n = 952) obtained via international collaboration were genotyped using the Illumina HumanCoreExome chip. Additional non-assayed HLA loci and genome-wide SNPs were imputed.
Results
HLA-DRB1*03:01 was confirmed as the classical HLA allele most strongly associated with JDM (OR 1.66; 95% CI 1.46, 1.89; P = 1.4 × 10−14), with an independent association at HLA-C*02:02 (OR = 1.74; 95% CI 1.42, 2.13, P = 7.13 × 10−8). Analyses of amino acid positions within HLA-DRB1 indicated the strongest association was at position 37 (omnibus P = 3.3 × 10−19), with suggestive evidence this association was independent of position 74 (omnibus P = 5.1 × 10−5), the position most strongly associated with adult-onset DM. Conditional analyses also suggested the association at position 37 of HLA-DRB1 was independent of some alleles of the Caucasian HLA 8.1 ancestral haplotype (AH8.1) such as HLA-DQB1*02:01 (OR = 1.62; 95% CI 1.36, 1.93; P = 8.70 × 10−8), but not HLA-DRB1*03:01 (OR = 1.49; 95% CR 1.24, 1.80; P = 2.24 × 10−5). No associations outside the HLA region were identified.
Conclusions
Our findings confirm previous associations with AH8.1 and HLA-DRB1*03:01, HLA-C*02:02 and identify a novel association with amino acid position 37 within HLA-DRB1 which may distinguish JDM from adult DM.
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Affiliation(s)
- Claire T Deakin
- Infection, Immunity and Inflammation Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
- Centre for Adolescent Rheumatology Versus Arthritis at UCL, UCL Hospital and Great Ormond Street Hospital, London, UK
- NIHR Biomedical Research Centre at Great Ormond Street Hospital, London, UK
| | - John Bowes
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- National Institute of Health Research Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Lisa G Rider
- Environmental Autoimmunity Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Bethesda, Maryland, USA
| | - Frederick W Miller
- Environmental Autoimmunity Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Bethesda, Maryland, USA
| | - Lauren M Pachman
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
| | - Helga Sanner
- Department of Rheumatology, University of Oslo, Oslo, Norway
- Oslo New University College, Oslo, Norway
| | | | - Gulnara Mamyrova
- Division of Rheumatology, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rodolfo Curiel
- Division of Rheumatology, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Brian M Feldman
- Division of Rheumatology, Department of Pediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Adam M Huber
- IWK Health Centre and Dalhousie University, Halifax, Nova Scotia, Canada
| | - Ann M Reed
- Pediatrics, Duke University, Durham, North Carolina, USA
| | - Heinrike Schmeling
- Alberta Children's Hospital and Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Charlotte G Cook
- Infection, Immunity and Inflammation Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Lucy R Marshall
- Infection, Immunity and Inflammation Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
- Centre for Adolescent Rheumatology Versus Arthritis at UCL, UCL Hospital and Great Ormond Street Hospital, London, UK
- NIHR Biomedical Research Centre at Great Ormond Street Hospital, London, UK
| | - Meredyth G Ll Wilkinson
- Infection, Immunity and Inflammation Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
- Centre for Adolescent Rheumatology Versus Arthritis at UCL, UCL Hospital and Great Ormond Street Hospital, London, UK
- NIHR Biomedical Research Centre at Great Ormond Street Hospital, London, UK
| | - Stephen Eyre
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- National Institute of Health Research Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Soumya Raychaudhuri
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- National Institute of Health Research Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Lucy R Wedderburn
- Infection, Immunity and Inflammation Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
- Centre for Adolescent Rheumatology Versus Arthritis at UCL, UCL Hospital and Great Ormond Street Hospital, London, UK
- NIHR Biomedical Research Centre at Great Ormond Street Hospital, London, UK
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236
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Gormley M, Dudding T, Kachuri L, Burrows K, Chong AHW, Martin RM, Thomas SJ, Tyrrell J, Ness AR, Brennan P, Munafò MR, Pring M, Boccia S, Olshan AF, Diergaarde B, Hung RJ, Liu G, Tajara EH, Severino P, Toporcov TN, Lacko M, Waterboer T, Brenner N, Smith GD, Vincent EE, Richmond RC. Investigating the effect of sexual behaviour on oropharyngeal cancer risk: a methodological assessment of Mendelian randomization. BMC Med 2022; 20:40. [PMID: 35094705 PMCID: PMC8802428 DOI: 10.1186/s12916-022-02233-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 01/04/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Human papilloma virus infection is known to influence oropharyngeal cancer (OPC) risk, likely via sexual transmission. However, sexual behaviour has been correlated with other risk factors including smoking and alcohol, meaning independent effects are difficult to establish. We aimed to evaluate the causal effect of sexual behaviour on the risk of OPC using Mendelian randomization (MR). METHODS Genetic variants robustly associated with age at first sex (AFS) and the number of sexual partners (NSP) were used to perform both univariable and multivariable MR analyses with summary data on 2641 OPC cases and 6585 controls, obtained from the largest available genome-wide association studies (GWAS). Given the potential for genetic pleiotropy, we performed a number of sensitivity analyses: (i) MR methods to account for horizontal pleiotropy, (ii) MR of sexual behaviours on positive (cervical cancer and seropositivity for Chlamydia trachomatis) and negative control outcomes (lung and oral cancer), (iii) Causal Analysis Using Summary Effect estimates (CAUSE), to account for correlated and uncorrelated horizontal pleiotropic effects, (iv) multivariable MR analysis to account for the effects of smoking, alcohol, risk tolerance and educational attainment. RESULTS In univariable MR, we found evidence supportive of an effect of both later AFS (IVW OR = 0.4, 95%CI (0.3, 0.7), per standard deviation (SD), p = < 0.001) and increasing NSP (IVW OR = 2.2, 95%CI (1.3, 3.8) per SD, p = < 0.001) on OPC risk. These effects were largely robust to sensitivity analyses accounting for horizontal pleiotropy. However, negative control analysis suggested potential violation of the core MR assumptions and subsequent CAUSE analysis implicated pleiotropy of the genetic instruments used to proxy sexual behaviours. Finally, there was some attenuation of the univariable MR results in the multivariable models (AFS IVW OR = 0.7, 95%CI (0.4, 1.2), p = 0.21; NSP IVW OR = 0.9, 95%CI (0.5 1.7), p = 0.76). CONCLUSIONS Despite using genetic variants strongly related sexual behaviour traits in large-scale GWAS, we found evidence for correlated pleiotropy. This emphasizes a need for multivariable approaches and the triangulation of evidence when performing MR of complex behavioural traits.
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Affiliation(s)
- Mark Gormley
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Bristol Dental Hospital and School, University of Bristol, Bristol, UK.
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Tom Dudding
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Dental Hospital and School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Linda Kachuri
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, USA
| | - Kimberley Burrows
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Amanda H W Chong
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- University Hospitals Bristol and Weston NHS Foundation Trust National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Steven J Thomas
- Bristol Dental Hospital and School, University of Bristol, Bristol, UK
- University Hospitals Bristol and Weston NHS Foundation Trust National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Jessica Tyrrell
- University of Exeter Medical School, RILD Building, RD&E Hospital, Exeter, UK
| | - Andrew R Ness
- University Hospitals Bristol and Weston NHS Foundation Trust National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Paul Brennan
- Genetic Epidemiology Group, World Health Organization, International Agency for Research on Cancer, Lyon, France
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Psychological Science, Faculty of Life Sciences, University of Bristol, Bristol, UK
| | - Miranda Pring
- Bristol Dental Hospital and School, University of Bristol, Bristol, UK
| | - Stefania Boccia
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italia
- Department of Woman and Child Health and Public Health - Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, USA
| | - Brenda Diergaarde
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, and UPMC Hillman Cancer Center, Pittsburgh, USA
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Geoffrey Liu
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Princess Margaret Cancer Centre, Toronto, Canada
| | - Eloiza H Tajara
- Department of Molecular Biology, School of Medicine of São José do Rio Preto, São Paulo, Brazil
| | - Patricia Severino
- Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Tatiana N Toporcov
- Department of Epidemiology, School of Public Health, University of São Paulo, São Paulo, Brazil
| | - Martin Lacko
- Department of Otorhinolaryngology and Head and Neck Surgery, Research Institute GROW, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Tim Waterboer
- Infections and Cancer Epidemiology, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - Nicole Brenner
- Infections and Cancer Epidemiology, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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237
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Zhong X, Su C, Fan Z. Empirical Bayes PCA in high dimensions. J R Stat Soc Series B Stat Methodol 2022. [DOI: 10.1111/rssb.12490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Xinyi Zhong
- Department of Statistics and Data ScienceYale University New HavenUSA
| | - Chang Su
- Department of BiostatisticsYale University New HavenUSA
| | - Zhou Fan
- Department of Statistics and Data ScienceYale University New HavenUSA
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238
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Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease. Biomedicines 2022; 10:biomedicines10020259. [PMID: 35203469 PMCID: PMC8868589 DOI: 10.3390/biomedicines10020259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/22/2022] [Accepted: 01/23/2022] [Indexed: 11/17/2022] Open
Abstract
The study was designed to evaluate putative mechanisms by which lipid-associated loci identified by genome-wide association studies (GWAS) are involved in the molecular pathogenesis of coronary artery disease (CAD) using a comprehensive statistical and bioinformatics analysis. A total of 1700 unrelated individuals of Slavic origin from the Central Russia, including 991 CAD patients and 709 healthy controls were examined. Sixteen lipid-associated GWAS loci were selected from European studies and genotyped using the MassArray-4 system. The polymorphisms were associated with plasma lipids such as total cholesterol (rs12328675, rs4846914, rs55730499, and rs838880), LDL-cholesterol (rs3764261, rs55730499, rs1689800, and rs838880), HDL-cholesterol (rs3764261) as well as carotid intima-media thickness/CIMT (rs12328675, rs11220463, and rs1689800). Polymorphisms such as rs4420638 of APOC1 (p = 0.009), rs55730499 of LPA (p = 0.0007), rs3136441 of F2 (p < 0.0001), and rs6065906 of PLTP (p = 0.002) showed significant associations with the risk of CAD, regardless of sex, age, and body mass index. A majority of the observed associations were successfully replicated in large independent cohorts. Bioinformatics analysis allowed establishing (1) phenotype-specific and shared epistatic gene–gene and gene–smoking interactions contributing to all studied cardiovascular phenotypes; (2) lipid-associated GWAS loci might be allele-specific binding sites for transcription factors from gene regulatory networks controlling multifaceted molecular mechanisms of atherosclerosis.
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239
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Bergen DJM, Tong Q, Shukla A, Newham E, Zethof J, Lundberg M, Ryan R, Youlten SE, Frysz M, Croucher PI, Flik G, Richardson RJ, Kemp JP, Hammond CL, Metz JR. Regenerating zebrafish scales express a subset of evolutionary conserved genes involved in human skeletal disease. BMC Biol 2022; 20:21. [PMID: 35057801 PMCID: PMC8780716 DOI: 10.1186/s12915-021-01209-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 12/07/2021] [Indexed: 12/23/2022] Open
Abstract
Background Scales are mineralised exoskeletal structures that are part of the dermal skeleton. Scales have been mostly lost during evolution of terrestrial vertebrates whilst bony fish have retained a mineralised dermal skeleton in the form of fin rays and scales. Each scale is a mineralised collagen plate that is decorated with both matrix-building and resorbing cells. When removed, an ontogenetic scale is quickly replaced following differentiation of the scale pocket-lining cells that regenerate a scale. Processes promoting de novo matrix formation and mineralisation initiated during scale regeneration are poorly understood. Therefore, we performed transcriptomic analysis to determine gene networks and their pathways involved in dermal scale regeneration. Results We defined the transcriptomic profiles of ontogenetic and regenerating scales of zebrafish and identified 604 differentially expressed genes (DEGs). These were enriched for extracellular matrix, ossification, and cell adhesion pathways, but not in enamel or dentin formation processes indicating that scales are reminiscent to bone. Hypergeometric tests involving monogenetic skeletal disorders showed that DEGs were strongly enriched for human orthologues that are mutated in low bone mass and abnormal bone mineralisation diseases (P< 2× 10−3). The DEGs were also enriched for human orthologues associated with polygenetic skeletal traits, including height (P< 6× 10−4), and estimated bone mineral density (eBMD, P< 2× 10−5). Zebrafish mutants of two human orthologues that were robustly associated with height (COL11A2, P=6× 10−24) or eBMD (SPP1, P=6× 10−20) showed both exo- and endo- skeletal abnormalities as predicted by our genetic association analyses; col11a2Y228X/Y228X mutants showed exoskeletal and endoskeletal features consistent with abnormal growth, whereas spp1P160X/P160X mutants predominantly showed mineralisation defects. Conclusion We show that scales have a strong osteogenic expression profile comparable to other elements of the dermal skeleton, enriched in genes that favour collagen matrix growth. Despite the many differences between scale and endoskeletal developmental processes, we also show that zebrafish scales express an evolutionarily conserved sub-population of genes that are relevant to human skeletal disease. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-021-01209-8.
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Klassmann A, Gautier M. Detecting selection using extended haplotype homozygosity (EHH)-based statistics in unphased or unpolarized data. PLoS One 2022; 17:e0262024. [PMID: 35041674 PMCID: PMC8765611 DOI: 10.1371/journal.pone.0262024] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 12/15/2021] [Indexed: 12/19/2022] Open
Abstract
Analysis of population genetic data often includes a search for genomic regions with signs of recent positive selection. One of such approaches involves the concept of extended haplotype homozygosity (EHH) and its associated statistics. These statistics typically require phased haplotypes, and some of them necessitate polarized variants. Here, we unify and extend previously proposed modifications to loosen these requirements. We compare the modified versions with the original ones by measuring the false discovery rate in simulated whole-genome scans and by quantifying the overlap of inferred candidate regions in empirical data. We find that phasing information is indispensable for accurate estimation of within-population statistics (for all but very large samples) and of cross-population statistics for small samples. Ancestry information, in contrast, is of lesser importance for both types of statistic. Our publicly available R package rehh incorporates the modified statistics presented here.
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Affiliation(s)
| | - Mathieu Gautier
- CBGP, Univ Montpellier, CIRAD, INRAE, IRD, Institut Agro, Montpellier, France
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241
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Liu Y, Lv Y, Zarrei M, Dong R, Yang X, Higginbotham EJ, Li Y, Zhao D, Song F, Yang Y, Zhang H, Wang Y, Scherer SW, Gai Z. Chromosomal microarray analysis of 410 Han Chinese patients with autism spectrum disorder or unexplained intellectual disability and developmental delay. NPJ Genom Med 2022; 7:1. [PMID: 35022430 PMCID: PMC8755789 DOI: 10.1038/s41525-021-00271-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 11/09/2021] [Indexed: 12/20/2022] Open
Abstract
Copy number variants (CNVs) are recognized as a crucial genetic cause of neurodevelopmental disorders (NDDs). Chromosomal microarray analysis (CMA), the first-tier diagnostic test for individuals with NDDs, has been utilized to detect CNVs in clinical practice, but most reports are still from populations of European ancestry. To contribute more worldwide clinical genomics data, we investigated the genetic etiology of 410 Han Chinese patients with NDDs (151 with autism and 259 with unexplained intellectual disability (ID) and developmental delay (DD)) using CMA (Affymetrix) after G-banding karyotyping. Among all the NDD patients, 109 (26.6%) carried clinically relevant CNVs or uniparental disomies (UPDs), and 8 (2.0%) had aneuploidies (6 with trisomy 21 syndrome, 1 with 47,XXY, 1 with 47,XYY). In total, we found 129 clinically relevant CNVs and UPDs, including 32 CNVs in 30 ASD patients, and 92 CNVs and 5 UPDs in 79 ID/DD cases. When excluding the eight patients with aneuploidies, the diagnostic yield of pathogenic and likely pathogenic CNVs and UPDs was 20.9% for all NDDs (84/402), 3.3% in ASD (5/151), and 31.5% in ID/DD (79/251). When aneuploidies were included, the diagnostic yield increased to 22.4% for all NDDs (92/410), and 33.6% for ID/DD (87/259). We identified a de novo CNV in 14.9% (60/402) of subjects with NDDs. Interestingly, a higher diagnostic yield was observed in females (31.3%, 40/128) compared to males (16.1%, 44/274) for all NDDs (P = 4.8 × 10-4), suggesting that a female protective mechanism exists for deleterious CNVs and UPDs.
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Affiliation(s)
- Yi Liu
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Yuqiang Lv
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Mehdi Zarrei
- The Centre for Applied Genomics and Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Rui Dong
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Xiaomeng Yang
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Edward J Higginbotham
- The Centre for Applied Genomics and Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Yue Li
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Dongmei Zhao
- Pediatric Health Care Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Fengling Song
- Pediatric Health Care Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Yali Yang
- Rehabilitation Center, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Haiyan Zhang
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Ying Wang
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Stephen W Scherer
- The Centre for Applied Genomics and Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada. .,McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A1, Canada.
| | - Zhongtao Gai
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China.
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242
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Choquet H, Li W, Yin J, Bradley R, Hoffmann TJ, Nandakumar P, Mostaedi R, Tian C, Ahituv N, Jorgenson E. Ancestry- and sex-specific effects underlying inguinal hernia susceptibility identified in a multiethnic genome-wide association study meta-analysis. Hum Mol Genet 2022; 31:2279-2293. [PMID: 35022708 PMCID: PMC9262393 DOI: 10.1093/hmg/ddac003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 12/06/2021] [Accepted: 01/04/2022] [Indexed: 12/03/2022] Open
Abstract
Inguinal hernias are some of the most frequently diagnosed conditions in clinical practice and inguinal hernia repair is the most common procedure performed by general surgeons. Studies of inguinal hernias in non-European populations are lacking, though it is expected that such studies could identify novel loci. Further, the cumulative lifetime incidence of inguinal hernia is nine times greater in men than women, however, it is not clear why this difference exists. We conducted a genome-wide association meta-analysis of inguinal hernia risk across 513 120 individuals (35 774 cases and 477 346 controls) of Hispanic/Latino, African, Asian and European descent, with replication in 728 418 participants (33 491 cases and 694 927 controls) from the 23andMe, Inc dataset. We identified 63 genome-wide significant loci (P < 5 × 10−8), including 41 novel. Ancestry-specific analyses identified two loci (LYPLAL1-AS1/SLC30A10 and STXBP6-NOVA1) in African ancestry individuals. Sex-stratified analyses identified two loci (MYO1D and ZBTB7C) that are specific to women, and four (EBF2, EMX2/RAB11FIP2, VCL and FAM9A/FAM9B) that are specific to men. Functional experiments demonstrated that several of the associated regions (EFEMP1 and LYPLAL1-SLC30A10) function as enhancers and show differential activity between risk and reference alleles. Our study highlights the importance of large-scale genomic studies in ancestrally diverse populations for identifying ancestry-specific inguinal hernia susceptibility loci and provides novel biological insights into inguinal hernia etiology.
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Affiliation(s)
- Hélène Choquet
- To whom correspondence should be addressed at: KPNC, Division of Research, 2000 Broadway, Oakland, CA 94612, USA. Tel: +1 5108915972; Fax: +1 5108913508;
| | - Weiyu Li
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco (UCSF), San Francisco, CA 94158, USA
| | - Jie Yin
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, CA 94612, USA
| | - Rachael Bradley
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco (UCSF), San Francisco, CA 94158, USA
| | - Thomas J Hoffmann
- Institute for Human Genetics, UCSF, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, UCSF, San Francisco, CA 94158, USA
| | | | | | | | - Chao Tian
- 23andMe Inc, Sunnyvale, CA 94086, USA
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243
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Colomer-Vilaplana A, Murga-Moreno J, Canalda-Baltrons A, Inserte C, Soto D, Coronado-Zamora M, Barbadilla A, Casillas S. PopHumanVar: an interactive application for the functional characterization and prioritization of adaptive genomic variants in humans. Nucleic Acids Res 2022; 50:D1069-D1076. [PMID: 34664660 PMCID: PMC8728255 DOI: 10.1093/nar/gkab925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/17/2021] [Accepted: 09/28/2021] [Indexed: 12/22/2022] Open
Abstract
Adaptive challenges that humans faced as they expanded across the globe left specific molecular footprints that can be decoded in our today's genomes. Different sets of metrics are used to identify genomic regions that have undergone selection. However, there are fewer methods capable of pinpointing the allele ultimately responsible for this selection. Here, we present PopHumanVar, an interactive online application that is designed to facilitate the exploration and thorough analysis of candidate genomic regions by integrating both functional and population genomics data currently available. PopHumanVar generates useful summary reports of prioritized variants that are putatively causal of recent selective sweeps. It compiles data and graphically represents different layers of information, including natural selection statistics, as well as functional annotations and genealogical estimations of variant age, for biallelic single nucleotide variants (SNVs) of the 1000 Genomes Project phase 3. Specifically, PopHumanVar amasses SNV-based information from GEVA, SnpEFF, GWAS Catalog, ClinVar, RegulomeDB and DisGeNET databases, as well as accurate estimations of iHS, nSL and iSAFE statistics. Notably, PopHumanVar can successfully identify known causal variants of frequently reported candidate selection regions, including EDAR in East-Asians, ACKR1 (DARC) in Africans and LCT/MCM6 in Europeans. PopHumanVar is open and freely available at https://pophumanvar.uab.cat.
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Affiliation(s)
- Aina Colomer-Vilaplana
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Jesús Murga-Moreno
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Aleix Canalda-Baltrons
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Clara Inserte
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Daniel Soto
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Marta Coronado-Zamora
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
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Zhang H, Xiu X, Xue A, Yang Y, Yang Y, Zhao H. Mendelian randomization study reveals a population-specific putative causal effect of type 2 diabetes in risk of cataract. Int J Epidemiol 2022; 50:2024-2037. [PMID: 34999863 DOI: 10.1093/ije/dyab175] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 08/03/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The epidemiological association between type 2 diabetes and cataract has been well established. However, it remains unclear whether the two diseases share a genetic basis, and if so, whether this reflects a putative causal relationship. METHODS We used East Asian population-based genome-wide association studies (GWAS) summary statistics of type 2 diabetes (Ncase = 36 614, Ncontrol = 155 150) and cataract (Ncase = 24 622, Ncontrol = 187 831) to comprehensively investigate the shared genetics between the two diseases. We performed: (i) linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (ρ-HESS) to estimate the genetic correlation and local genetic correlation pattern between type 2 diabetes and cataract; (ii) multiple Mendelian randomization (MR) analyses to infer the putative causality between type 2 diabetes and cataract; and (iii) summary-data-based Mendelian randomization (SMR) to identify candidate risk genes underling the putative causality. Moreover, to investigate the extent of the population-specific genetic effect size underlying the shared genetics between type 2 diabetes and cataract, we applied the same analytical pipeline to perform a comparative analysis on European population-based GWAS of type 2 diabetes (Ncase = 62 892, Ncontrol = 596 424) and cataract (Ncase = 5045, Ncontrol = 356 096). RESULTS Using East Asian population-based GWAS summary data, we observed a strong genetic correlation [rg = 0.58, 95% confidence interval (CI) = 0.33, 0.83), P-value = 5.60 × 10-6] between type 2 diabetes and cataract. Both ρ-HESS and multiple MR methods consistently showed a putative causal effect of type 2 diabetes on cataract, with estimated liability-scale MR odds ratios (ORs) at around 1.10 (95% CI = 1.06, 1.17). In contrast, no evidence supports a causal effect of cataract on type 2 diabetes. SMR analysis identified two novel genes MIR4453HG (βSMR = -0.34, 95% CI = -0.46, -0.22, P-value = 6.41 × 10-8) and KCNK17 (βSMR = -0.07, 95% CI = -0.09, -0.05, P-value = 2.49 × 10-10), whose expression levels were likely involved in the putative causality of type 2 diabetes on cataract. On the contrary, our comparative analysis on European population provided universally weak evidence on the genetic correlation and causal relationship between the two diseases. CONCLUSIONS Our results provided robust evidence supporting a putative causal effect of type 2 diabetes on the risk of cataract in East Asians, and revealed potential genetic heterogeneity in the shared genetics underlying type 2 diabetes and cataract between East Asians and Europeans. These findings posed new paths on guiding the prevention and early-stage diagnosis of cataract in type 2 diabetes patients.
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Affiliation(s)
- Haoyang Zhang
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China
- Department of Medical Research Center, Sun Yat-sen Memorial Hospital, and Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China
| | - Xuehao Xiu
- Department of Medical Research Center, Sun Yat-sen Memorial Hospital, and Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China
| | - Angli Xue
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Yuedong Yang
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China
| | - Yuanhao Yang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Mater Research, Translational Research Institute, Brisbane, QLD, Australia
| | - Huiying Zhao
- Department of Medical Research Center, Sun Yat-sen Memorial Hospital, and Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China
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245
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Li J, Glover JD, Zhang H, Peng M, Tan J, Mallick CB, Hou D, Yang Y, Wu S, Liu Y, Peng Q, Zheng SC, Crosse EI, Medvinsky A, Anderson RA, Brown H, Yuan Z, Zhou S, Xu Y, Kemp JP, Ho YYW, Loesch DZ, Wang L, Li Y, Tang S, Wu X, Walters RG, Lin K, Meng R, Lv J, Chernus JM, Neiswanger K, Feingold E, Evans DM, Medland SE, Martin NG, Weinberg SM, Marazita ML, Chen G, Chen Z, Zhou Y, Cheeseman M, Wang L, Jin L, Headon DJ, Wang S. Limb development genes underlie variation in human fingerprint patterns. Cell 2022; 185:95-112.e18. [PMID: 34995520 PMCID: PMC8740935 DOI: 10.1016/j.cell.2021.12.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 10/20/2021] [Accepted: 12/08/2021] [Indexed: 12/12/2022]
Abstract
Fingerprints are of long-standing practical and cultural interest, but little is known about the mechanisms that underlie their variation. Using genome-wide scans in Han Chinese cohorts, we identified 18 loci associated with fingerprint type across the digits, including a genetic basis for the long-recognized “pattern-block” correlations among the middle three digits. In particular, we identified a variant near EVI1 that alters regulatory activity and established a role for EVI1 in dermatoglyph patterning in mice. Dynamic EVI1 expression during human development supports its role in shaping the limbs and digits, rather than influencing skin patterning directly. Trans-ethnic meta-analysis identified 43 fingerprint-associated loci, with nearby genes being strongly enriched for general limb development pathways. We also found that fingerprint patterns were genetically correlated with hand proportions. Taken together, these findings support the key role of limb development genes in influencing the outcome of fingerprint patterning. GWAS identifies variants associated with fingerprint type across all digits Fingerprint-associated genes are strongly enriched for limb development functions Evi1 alters dermatoglyphs in mice by modulating limb rather than skin development Fingerprint patterns are genetically correlated with hand and finger proportions
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Affiliation(s)
- Jinxi Li
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, and Human Phenome Institute, Fudan University, Shanghai 200438, PRC; CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC
| | - James D Glover
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Haiguo Zhang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200438, PRC
| | - Meifang Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200438, PRC
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200438, PRC
| | - Chandana Basu Mallick
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK; Centre for Genetic Disorders, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India
| | - Dan Hou
- Chinese Academy of Sciences Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200438, PRC
| | - Sijie Wu
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, and Human Phenome Institute, Fudan University, Shanghai 200438, PRC; CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC
| | - Yu Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC
| | - Shijie C Zheng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC
| | - Edie I Crosse
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | | | - Richard A Anderson
- MRC Centre for Reproductive Health, Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Helen Brown
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, PRC
| | - Shen Zhou
- Shanghai Foreign Language School, Shanghai 200083, PRC
| | - Yanqing Xu
- Forest Ridge School of the Sacred Heart, Bellevue, WA 98006, USA
| | - John P Kemp
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, QLD, Australia
| | - Yvonne Y W Ho
- QIMR Berghofer Medical Rese Institute, Brisbane, QLD, Australia
| | - Danuta Z Loesch
- Psychology Department, La Trobe University, Melbourne, VIC, Australia
| | | | | | | | - Xiaoli Wu
- WeGene, Shenzhen, Guangdong 518040, PRC
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Ruogu Meng
- Center for Data Science in Health and Medicine, Peking University, Beijing 100191, PRC
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, PRC
| | - Jonathan M Chernus
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Katherine Neiswanger
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA 15219, USA
| | - Eleanor Feingold
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - David M Evans
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, QLD, Australia; Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Sarah E Medland
- QIMR Berghofer Medical Rese Institute, Brisbane, QLD, Australia
| | | | - Seth M Weinberg
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA; Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA 15219, USA; Department of Anthropology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Mary L Marazita
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA; Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA 15219, USA; Clinical and Translational Science, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Gang Chen
- WeGene, Shenzhen, Guangdong 518040, PRC
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Yong Zhou
- Clinical Research Institute, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PRC
| | - Michael Cheeseman
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Lan Wang
- Chinese Academy of Sciences Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, and Human Phenome Institute, Fudan University, Shanghai 200438, PRC; CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, PRC.
| | - Denis J Headon
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, PRC; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, PRC.
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Bellou E, Escott-Price V. Are Alzheimer's and coronary artery diseases genetically related to longevity? Front Psychiatry 2022; 13:1102347. [PMID: 36684006 PMCID: PMC9859055 DOI: 10.3389/fpsyt.2022.1102347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 12/12/2022] [Indexed: 01/07/2023] Open
Abstract
INTRODUCTION In the last decade researchers have attempted to investigate the shared genetic architecture of longevity and age-related diseases and assess whether the increased longevity in certain people is due to protective alleles in the risk genes for a particular condition or whether there are specific "longevity" genes increasing the lifespan independently of age-related conditions' risk genes. The aim of this study was to investigate the shared genetic component between longevity and two age-related conditions. METHODS We performed a cross-trait meta-analysis of publicly available genome-wide data for Alzheimer's disease, coronary artery disease and longevity using a subset-based approach provided by the R package ASSET. RESULTS Despite the lack of strong genetic correlation between longevity and the two diseases, we identified 38 genome-wide significant lead SNPs across 22 independent genomic loci. Of them 6 were found to be potentially shared among the three traits mapping to genes including DAB2IP, DNM2, FCHO1, CLPTM1, and SNRPD2. We also identified 19 novel genome-wide associations for the individual traits in this study. Functional annotations and biological pathway enrichment analyses suggested that pleiotropic variants are involved in clathrin-mediated endocytosis and plasma lipoprotein and neurotransmitter clearance processes. DISCUSSION In summary, we have been able to advance in the knowledge of the genetic overlap existing among longevity and the two most common age-related disorders.
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Affiliation(s)
- Eftychia Bellou
- UK Dementia Research Institute, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Valentina Escott-Price
- Division of Neuroscience and Mental Health, School of Medicine, Cardiff University, Cardiff, United Kingdom
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Working memory and reaction time variability mediate the relationship between polygenic risk and ADHD traits in a general population sample. Mol Psychiatry 2022; 27:5028-5037. [PMID: 36151456 PMCID: PMC9763105 DOI: 10.1038/s41380-022-01775-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 08/19/2022] [Accepted: 09/02/2022] [Indexed: 01/14/2023]
Abstract
Endophenotypes are heritable and quantifiable traits indexing genetic liability for a disorder. Here, we examined three potential endophenotypes, working memory function, response inhibition, and reaction time variability, for attention-deficit hyperactivity disorder (ADHD) measured as a dimensional latent trait in a large general population sample derived from the Adolescent Brain Cognitive DevelopmentSM Study. The genetic risk for ADHD was estimated using polygenic risk scores (PRS) whereas ADHD traits were quantified as a dimensional continuum using Bartlett factor score estimates, derived from Attention Problems items from the Child Behaviour Checklist and Effortful Control items from the Early Adolescent Temperament Questionnaire-Revised. The three candidate cognitive endophenotypes were quantified using task-based performance measures. Higher ADHD PRSs were associated with higher ADHD traits, as well as poorer working memory performance and increased reaction time variability. Lower working memory performance, poorer response inhibition, and increased reaction time variability were associated with more pronounced ADHD traits. Working memory and reaction time variability partially statistically mediated the relationship between ADHD PRS and ADHD traits, explaining 14% and 16% of the association, respectively. The mediation effect was specific to the genetic risk for ADHD and did not generalise to genetic risk for four other major psychiatric disorders. Together, these findings provide robust evidence from a large general population sample that working memory and reaction time variability can be considered endophenotypes for ADHD that mediate the relationship between ADHD PRS and ADHD traits.
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248
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Matoba N, Love MI, Stein JL. Evaluating brain structure traits as endophenotypes using polygenicity and discoverability. Hum Brain Mapp 2022; 43:329-340. [PMID: 33098356 PMCID: PMC8675430 DOI: 10.1002/hbm.25257] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 09/28/2020] [Accepted: 10/11/2020] [Indexed: 12/24/2022] Open
Abstract
Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively "closer to the underlying biology." Genome-wide association studies from large sample sizes allow for the comparison of common variant genetic architectures between traits to test the evidence supporting this claim. Endophenotypes, compared to neuropsychiatric disorders, are hypothesized to have less polygenicity, with greater effect size of each susceptible SNP, requiring smaller sample sizes to discover them. Here, we compare polygenicity and discoverability of brain structure traits, neuropsychiatric disorders, and other traits (91 in total) to directly test this hypothesis. We found reduced polygenicity (FDR = 0.01) and increased discoverability (FDR = 3.68 × 10-9 ) of cortical brain structure traits, as compared to aggregated estimates of multiple neuropsychiatric disorders. We predict that ~8 M individuals will be required to explain the full heritability of cortical surface area by genome-wide significant SNPs, whereas sample sizes over 20 M will be required to explain the full heritability of depression. In conclusion, our findings are consistent with brain structure satisfying the higher power criterion of endophenotypes.
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Affiliation(s)
- Nana Matoba
- Department of GeneticsUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- UNC Neuroscience CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Michael I. Love
- Department of GeneticsUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of BiostatisticsUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Jason L. Stein
- Department of GeneticsUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- UNC Neuroscience CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
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Nayyar A, Ahmed S. Donor Chimerism Study by Single Nucleotide Polymorphism using SYBR green based Real Time PCR. Pak J Med Sci 2021; 37:1795-1799. [PMID: 34912397 PMCID: PMC8613053 DOI: 10.12669/pjms.37.7.4203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 05/27/2021] [Accepted: 06/05/2021] [Indexed: 11/15/2022] Open
Abstract
Objective: To optimize and evaluate a real time PCR of Single Nucleotide Polymorphism by SYBR Green method for detection of donor chimerism after haematopoietic stem cell transplantation. Methods: This descriptive study was conducted at Genetic Resource Centre (GRC) Lab Rawalpindi from Oct 2017 - Dec 2019. A total of twenty patients of post haematopoietic stem cell transplant with various haematological disorders were studied to see the status of donor chimerism by using SNP real time PCR using SYBR Green method and short tandem repeat PCR. These patients had undergone allogeneic HSCT from HLA-matched sibling donors at Pakistan Institute of Medical Science and Armed Forces Bone Marrow Transplant Centre. Results: Real time PCR using SYBR Green was able to detect significant amount of chimerism in all 20 patients having undergone HSCT. Regarding precision of the real time PCR assay the mean value of donor chimerism was 94.1% (SD 3.96) and by STR PCR it was 95.1% (SD 1.41). The assay was found to be sensitive with a detection limit of <1%. Conclusion: Our results demonstrate that SNP analysis by SYBR Green real time PCR may be used for the evaluation of chimerism status in patients having undergone HSCT with a sensitivity of <1%. Hence donor chimerism by this sensitive method can be used in monitoring of chimerism in post-transplant patients with various haematological disorders.
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Affiliation(s)
- Ayesha Nayyar
- Dr. Ayesha Nayyar, M.Phil. Department of Pathology, Islamic International Medical College, Riphah International University, Islamabad, Pakistan
| | - Suhaib Ahmed
- Prof. Dr. Suhaib Ahmed, FCPS, PhD. Department of Pathology, Islamic International Medical College, Riphah International University, Islamabad, Pakistan
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Trinder M, Vikulova D, Pimstone S, Mancini GBJ, Brunham LR. Polygenic architecture and cardiovascular risk of familial combined hyperlipidemia. Atherosclerosis 2021; 340:35-43. [PMID: 34906840 DOI: 10.1016/j.atherosclerosis.2021.11.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 11/06/2021] [Accepted: 11/30/2021] [Indexed: 12/29/2022]
Abstract
BACKGROUND AND AIMS Familial combined hyperlipidemia (FCHL) is one of the most common inherited lipid phenotypes, characterized by elevated plasma concentrations of apolipoprotein B-100 and triglycerides. The genetic inheritance of FCHL remains poorly understood. The goals of this study were to investigate the polygenetic architecture and cardiovascular risk associated with FCHL. METHODS AND RESULTS We identified individuals with an FCHL phenotype among 349,222 unrelated participants of European ancestry in the UK Biobank using modified versions of 5 different diagnostic criteria. The prevalence of the FCHL phenotype was 11.44% (n = 39,961), 5.01% (n = 17,485), 1.48% (n = 5,153), 1.10% (n = 3,838), and 0.48% (n = 1,688) according to modified versions of the Consensus Conference, Dutch, Mexico, Brunzell, and Goldstein criteria, respectively. We performed discovery, case-control genome-wide association studies for these different FCHL criteria and identified 175 independent loci associated with FCHL at genome-wide significance. We investigated the association of genetic and clinical risk with FCHL and found that polygenic susceptibility to hypercholesterolemia or hypertriglyceridemia and features of metabolic syndrome were associated with greater prevalence of FCHL. Participants with an FCHL phenotype had a similar risk of incident coronary artery disease compared to participants with monogenic familial hypercholesterolemia (adjusted hazard ratio vs controls [95% confidence interval]: 2.72 [2.31-3.21] and 1.90 [1.30-2.78]). CONCLUSIONS These results suggest that, rather than being a single genetic entity, the FCHL phenotype represents a polygenic susceptibility to dyslipidemia in combination with metabolic abnormalities. The cardiovascular risk associated with an FCHL phenotype is similar to that of monogenic familial hypercholesterolemia, despite being ∼5x more common.
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Affiliation(s)
- Mark Trinder
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada; Experimental Medicine Program, University of British Columbia, Vancouver, British Columbia, Canada
| | - Diana Vikulova
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada; Experimental Medicine Program, University of British Columbia, Vancouver, British Columbia, Canada
| | - Simon Pimstone
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - G B John Mancini
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Liam R Brunham
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada; Experimental Medicine Program, University of British Columbia, Vancouver, British Columbia, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.
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