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2. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder

Author

Nievergelt, Caroline M., Maihofer, Adam X., Atkinson, Elizabeth G., Chen, Chia-Yen, Choi, Karmel W., Coleman, Jonathan R. I., Daskalakis, Nikolaos P., Duncan, Laramie E., Polimanti, Renato, Aaronson, Cindy, Amstadter, Ananda B., Andersen, Soren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegoviç, Esmina, Babić, Dragan, Bacanu, Silviu-Alin, Baker, Dewleen G., Batzler, Anthony, Beckham, Jean C., Belangero, Sintia, Benjet, Corina, Bergner, Carisa, Bierer, Linda M., Biernacka, Joanna M., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Brandolino, Amber, Breen, Gerome, Bressan, Rodrigo Affonseca, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Børglum, Anders D., Børte, Sigrid, Cahn, Leah, Calabrese, Joseph R., Caldas-de-Almeida, Jose Miguel, Chatzinakos, Chris, Cheema, Sheraz, Clouston, Sean A. P., Colodro-Conde, Lucía, Coombes, Brandon J., Cruz-Fuentes, Carlos S., Dale, Anders M., Dalvie, Shareefa, Davis, Lea K., Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Desarnaud, Frank, DiPietro, Christopher P., Disner, Seth G., Docherty, Anna R., Domschke, Katharina, Dyb, Grete, Kulenović, Alma Džubur, Edenberg, Howard J., Evans, Alexandra, Fabbri, Chiara, Fani, Negar, Farrer, Lindsay A., Feder, Adriana, Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles F., Goleva, Slavina B., Gordon, Scott D., Goçi, Aferdita, Grasser, Lana Ruvolo, Guindalini, Camila, Haas, Magali, Hagenaars, Saskia, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M. J., Hesselbrock, Victor, Hickie, Ian B., Hogan, Kelleigh, Hougaard, David Michael, Huang, Hailiang, Huckins, Laura M., Hveem, Kristian, Jakovljević, Miro, Javanbakht, Arash, Jenkins, Gregory D., Johnson, Jessica, Jones, Ian, Jovanovic, Tanja, Karstoft, Karen-Inge, Kaufman, Milissa L., Kennedy, James L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kotov, Roman, Kranzler, Henry R., Krebs, Kristi, Kremen, William S., Kuan, Pei-Fen, Lawford, Bruce R., Lebois, Lauren A. M., Lehto, Kelli, Levey, Daniel F., Lewis, Catrin, Liberzon, Israel, Linnstaedt, Sarah D., Logue, Mark W., Lori, Adriana, Lu, Yi, Luft, Benjamin J., Lupton, Michelle K., Luykx, Jurjen J., Makotkine, Iouri, Maples-Keller, Jessica L., Marchese, Shelby, Marmar, Charles, Martin, Nicholas G., Martínez-Levy, Gabriela A., McAloney, Kerrie, McFarlane, Alexander, McLaughlin, Katie A., McLean, Samuel A., Medland, Sarah E., Mehta, Divya, Meyers, Jacquelyn, Michopoulos, Vasiliki, Mikita, Elizabeth A., Milani, Lili, Milberg, William, Miller, Mark W., Morey, Rajendra A., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben Bo, Mufford, Mary S., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., Nugent, Nicole R., O’Donnell, Meaghan, Orcutt, Holly K., Pan, Pedro M., Panizzon, Matthew S., Pathak, Gita A., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Porjesz, Bernice, Powers, Abigail, Qin, Xue-Jun, Ratanatharathorn, Andrew, Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Kenneth J., Rung, Ariane, Runz, Heiko, Rutten, Bart P. F., de Viteri, Stacey Saenz, Salum, Giovanni Abrahão, Sampson, Laura, Sanchez, Sixto E., Santoro, Marcos, Seah, Carina, Seedat, Soraya, Seng, Julia S., Shabalin, Andrey, Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Sponheim, Scott R., Stein, Dan J., Stensland, Synne, Stevens, Jennifer S., Sumner, Jennifer A., Teicher, Martin H., Thompson, Wesley K., Tiwari, Arun K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., Valdimarsdóttir, Unnur, Van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan H., Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Waszczuk, Monika, Weber, Heike, Wendt, Frank R., Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winsvold, Bendik S., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Xia, Yan, Xiong, Ying, Yehuda, Rachel, Young, Keith A., Young, Ross McD, Zai, Clement C., Zai, Gwyneth C., Zervas, Mark, Zhao, Hongyu, Zoellner, Lori A., Zwart, John-Anker, deRoon-Cassini, Terri, van Rooij, Sanne J. H., van den Heuvel, Leigh L., Stein, Murray B., Ressler, Kerry J., and Koenen, Karestan C.

Published
2024
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3. GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.

Author

Docherty, Anna, Mullins, Niamh, Ashley-Koch, Allison, Qin, Xuejun, Coleman, Jonathan, Shabalin, Andrey, Kang, JooEun, Murnyak, Balasz, Wendt, Frank, Adams, Mark, Campos, Adrian, DiBlasi, Emily, Fullerton, Janice, Kranzler, Henry, Bakian, Amanda, Monson, Eric, Rentería, Miguel, Walss-Bass, Consuelo, Andreassen, Ole, Behera, Chittaranjan, Bulik, Cynthia, Edenberg, Howard, Kessler, Ronald, Mann, J, Nurnberger, John, Pistis, Giorgio, Streit, Fabian, Ursano, Robert, Polimanti, Renato, Dennis, Michelle, Garrett, Melanie, Hair, Lauren, Harvey, Philip, Hauser, Elizabeth, Hauser, Michael, Huffman, Jennifer, Jacobson, Daniel, Madduri, Ravi, McMahon, Benjamin, Oslin, David, Trafton, Jodie, Awasthi, Swapnil, Berrettini, Wade, Bohus, Martin, Chang, Xiao, Chen, Hsi-Chung, Chen, Wei, Christensen, Erik, Crow, Scott, Duriez, Philibert, Edwards, Alexis, Fernández-Aranda, Fernando, Galfalvy, Hanga, Gandal, Michael, Gorwood, Philip, Guo, Yiran, Hafferty, Jonathan, Hakonarson, Hakon, Halmi, Katherine, Hishimoto, Akitoyo, Jain, Sonia, Jamain, Stéphane, Jiménez-Murcia, Susana, Johnson, Craig, Kaplan, Allan, Kaye, Walter, Keel, Pamela, Kennedy, James, Kim, Minsoo, Klump, Kelly, Levey, Daniel, Li, Dong, Liao, Shih-Cheng, Lieb, Klaus, Lilenfeld, Lisa, Marshall, Christian, Mitchell, James, Okazaki, Satoshi, Otsuka, Ikuo, Pinto, Dalila, Powers, Abigail, Ramoz, Nicolas, Ripke, Stephan, Roepke, Stefan, Rozanov, Vsevolod, Scherer, Stephen, Schmahl, Christian, Sokolowski, Marcus, Starnawska, Anna, Strober, Michael, Su, Mei-Hsin, Thornton, Laura, Treasure, Janet, Ware, Erin, Watson, Hunna, Witt, Stephanie, Woodside, D, Yilmaz, Zeynep, Zillich, Lea, and Adolfsson, Rolf

Subjects
Biological Markers, Depressive Disorders, Genetics, Schizophrenia Spectrum and Other Psychotic Disorders, Self-Harm, Suicide, Humans, Genome-Wide Association Study, Suicide, Attempted, Depressive Disorder, Major, Risk Factors, Suicidal Ideation, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Genetic Loci
Abstract

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values

Published
2023

4. Game-Theoretic Methods for Analyzing the Security and Stability of Corporate Information Systems

Author

Konyukhovskiy, Pavel, Shabalin, Andrey, Brilly, Mitja, Advisory Editor, Hoalst-Pullen, Nancy, Advisory Editor, Leitner, Michael, Advisory Editor, Patterson, Mark W., Advisory Editor, Veress, Márton, Advisory Editor, Bakaev, Maxim, editor, Bolgov, Radomir, editor, Chugunov, Andrei V., editor, Pereira, Roberto, editor, R, Elakkiya, editor, and Zhang, Wei, editor

Published
2024
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6. Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms

Author

Jami, Eshim S, Hammerschlag, Anke R, Ip, Hill F, Allegrini, Andrea G, Benyamin, Beben, Border, Richard, Diemer, Elizabeth W, Jiang, Chang, Karhunen, Ville, Lu, Yi, Lu, Qing, Mallard, Travis T, Mishra, Pashupati P, Nolte, Ilja M, Palviainen, Teemu, Peterson, Roseann E, Sallis, Hannah M, Shabalin, Andrey A, Tate, Ashley E, Thiering, Elisabeth, Vilor-Tejedor, Natàlia, Wang, Carol, Zhou, Ang, Adkins, Daniel E, Alemany, Silvia, Ask, Helga, Chen, Qi, Corley, Robin P, Ehli, Erik A, Evans, Luke M, Havdahl, Alexandra, Hagenbeek, Fiona A, Hakulinen, Christian, Henders, Anjali K, Hottenga, Jouke Jan, Korhonen, Tellervo, Mamun, Abdullah, Marrington, Shelby, Neumann, Alexander, Rimfeld, Kaili, Rivadeneira, Fernando, Silberg, Judy L, van Beijsterveldt, Catharina E, Vuoksimaa, Eero, Whipp, Alyce M, Tong, Xiaoran, Andreassen, Ole A, Boomsma, Dorret I, Brown, Sandra A, Burt, S Alexandra, Copeland, William, Dick, Danielle M, Harden, K Paige, Harris, Kathleen Mullan, Hartman, Catharina A, Heinrich, Joachim, Hewitt, John K, Hopfer, Christian, Hypponen, Elina, Jarvelin, Marjo-Riitta, Kaprio, Jaakko, Keltikangas-Järvinen, Liisa, Klump, Kelly L, Krauter, Kenneth, Kuja-Halkola, Ralf, Larsson, Henrik, Lehtimäki, Terho, Lichtenstein, Paul, Lundström, Sebastian, Maes, Hermine H, Magnus, Per, Munafò, Marcus R, Najman, Jake M, Njølstad, Pål R, Oldehinkel, Albertine J, Pennell, Craig E, Plomin, Robert, Reichborn-Kjennerud, Ted, Reynolds, Chandra, Rose, Richard J, Smolen, Andrew, Snieder, Harold, Stallings, Michael, Standl, Marie, Sunyer, Jordi, Tiemeier, Henning, Wadsworth, Sally J, Wall, Tamara L, Whitehouse, Andrew JO, Williams, Gail M, Ystrøm, Eivind, Nivard, Michel G, Bartels, Meike, and Middeldorp, Christel M

Subjects
Biological Psychology, Psychology, Genetics, Pediatric, Brain Disorders, Serious Mental Illness, Mental Health, Human Genome, Depression, Mental Illness, Behavioral and Social Science, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Mental health, Adolescent, Adult, Aggression, Anxiety, Attention Deficit Disorder with Hyperactivity, Autistic Disorder, Bipolar Disorder, Child, Child, Preschool, Genome-Wide Association Study, Humans, Loneliness, Polymorphism, Single Nucleotide, Schizophrenia, Sleep Initiation and Maintenance Disorders, depression, anxiety, repeated measures, genetic epidemiology, molecular genetics, Medical and Health Sciences, Psychology and Cognitive Sciences, Developmental & Child Psychology, Clinical sciences, Paediatrics, Applied and developmental psychology
Abstract

ObjectiveTo investigate the genetic architecture of internalizing symptoms in childhood and adolescence.MethodIn 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument.ResultsThe meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa.ConclusionGenetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

Published
2022

7. Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes

Author

Han, Seonggyun, DiBlasi, Emily, Monson, Eric T., Shabalin, Andrey, Ferris, Elliott, Chen, Danli, Fraser, Alison, Yu, Zhe, Staley, Michael, Callor, W. Brandon, Christensen, Erik D., Crockett, David K., Li, Qingqin S., Willour, Virginia, Bakian, Amanda V., Keeshin, Brooks, Docherty, Anna R., Eilbeck, Karen, and Coon, Hilary

Published
2023
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8. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors.

Author

Mullins, Niamh, Kang, JooEun, Campos, Adrian I, Coleman, Jonathan RI, Edwards, Alexis C, Galfalvy, Hanga, Levey, Daniel F, Lori, Adriana, Shabalin, Andrey, Starnawska, Anna, Su, Mei-Hsin, Watson, Hunna J, Adams, Mark, Awasthi, Swapnil, Gandal, Michael, Hafferty, Jonathan D, Hishimoto, Akitoyo, Kim, Minsoo, Okazaki, Satoshi, Otsuka, Ikuo, Ripke, Stephan, Ware, Erin B, Bergen, Andrew W, Berrettini, Wade H, Bohus, Martin, Brandt, Harry, Chang, Xiao, Chen, Wei J, Chen, Hsi-Chung, Crawford, Steven, Crow, Scott, DiBlasi, Emily, Duriez, Philibert, Fernández-Aranda, Fernando, Fichter, Manfred M, Gallinger, Steven, Glatt, Stephen J, Gorwood, Philip, Guo, Yiran, Hakonarson, Hakon, Halmi, Katherine A, Hwu, Hai-Gwo, Jain, Sonia, Jamain, Stéphane, Jiménez-Murcia, Susana, Johnson, Craig, Kaplan, Allan S, Kaye, Walter H, Keel, Pamela K, Kennedy, James L, Klump, Kelly L, Li, Dong, Liao, Shih-Cheng, Lieb, Klaus, Lilenfeld, Lisa, Liu, Chih-Min, Magistretti, Pierre J, Marshall, Christian R, Mitchell, James E, Monson, Eric T, Myers, Richard M, Pinto, Dalila, Powers, Abigail, Ramoz, Nicolas, Roepke, Stefan, Rozanov, Vsevolod, Scherer, Stephen W, Schmahl, Christian, Sokolowski, Marcus, Strober, Michael, Thornton, Laura M, Treasure, Janet, Tsuang, Ming T, Witt, Stephanie H, Woodside, D Blake, Yilmaz, Zeynep, Zillich, Lea, Adolfsson, Rolf, Agartz, Ingrid, Air, Tracy M, Alda, Martin, Alfredsson, Lars, Andreassen, Ole A, Anjorin, Adebayo, Appadurai, Vivek, Soler Artigas, María, Van der Auwera, Sandra, Azevedo, M Helena, Bass, Nicholas, Bau, Claiton HD, Baune, Bernhard T, Bellivier, Frank, Berger, Klaus, Biernacka, Joanna M, Bigdeli, Tim B, Binder, Elisabeth B, Boehnke, Michael, Boks, Marco P, Bosch, Rosa, and Braff, David L

Subjects
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Eating Disorders Working Group of the Psychiatric Genomics Consortium, German Borderline Genomics Consortium, MVP Suicide Exemplar Workgroup, VA Million Veteran Program, Humans, Risk Factors, Suicide, Attempted, Mental Disorders, Depressive Disorder, Major, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Genetic correlation, Genome-wide association study, Pleiotropy, Polygenicity, Suicide, Suicide attempt, Human Genome, Behavioral and Social Science, Mental Health, Prevention, Genetics, Brain Disorders, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

BackgroundSuicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.MethodsWe conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.ResultsTwo loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.ConclusionsOur results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Published
2022

9. Genetic association study of childhood aggression across raters, instruments, and age.

Author

Ip, Hill, van der Laan, Camiel, Krapohl, Eva, Brikell, Isabell, Sánchez-Mora, Cristina, Nolte, Ilja, St Pourcain, Beate, Bolhuis, Koen, Palviainen, Teemu, Zafarmand, Hadi, Colodro-Conde, Lucía, Gordon, Scott, Zayats, Tetyana, Aliev, Fazil, Jiang, Chang, Wang, Carol, Saunders, Gretchen, Karhunen, Ville, Hammerschlag, Anke, Adkins, Daniel, Border, Richard, Peterson, Roseann, Prinz, Joseph, Thiering, Elisabeth, Seppälä, Ilkka, Vilor-Tejedor, Natàlia, Ahluwalia, Tarunveer, Day, Felix, Hottenga, Jouke-Jan, Allegrini, Andrea, Rimfeld, Kaili, Chen, Qi, Lu, Yi, Martin, Joanna, Soler Artigas, María, Rovira, Paula, Bosch, Rosa, Español, Gemma, Ramos Quiroga, Josep, Neumann, Alexander, Ensink, Judith, Grasby, Katrina, Morosoli, José, Tong, Xiaoran, Marrington, Shelby, Middeldorp, Christel, Scott, James, Vinkhuyzen, Anna, Shabalin, Andrey, Corley, Robin, Evans, Luke, Sugden, Karen, Alemany, Silvia, Sass, Lærke, Vinding, Rebecca, Ruth, Kate, Tyrrell, Jess, Davies, Gareth, Ehli, Erik, Hagenbeek, Fiona, De Zeeuw, Eveline, Van Beijsterveldt, Toos, Larsson, Henrik, Snieder, Harold, Verhulst, Frank, Amin, Najaf, Whipp, Alyce, Korhonen, Tellervo, Vuoksimaa, Eero, Rose, Richard, Uitterlinden, André, Heath, Andrew, Madden, Pamela, Haavik, Jan, Harris, Jennifer, Helgeland, Øyvind, Johansson, Stefan, Knudsen, Gun, Njolstad, Pal, Lu, Qing, Rodriguez, Alina, Henders, Anjali, Mamun, Abdullah, Najman, Jackob, Brown, Sandy, Hopfer, Christian, Krauter, Kenneth, Reynolds, Chandra, Smolen, Andrew, Stallings, Michael, Wadsworth, Sally, Wall, Tamara, Silberg, Judy, Miller, Allison, Keltikangas-Järvinen, Liisa, Hakulinen, Christian, Pulkki-Råback, Laura, Havdahl, Alexandra, Magnus, Per, and Raitakari, Olli

Subjects
Adolescent, Aggression, Child, Child, Preschool, Female, Genetic Association Studies, Genome-Wide Association Study, Humans, Infant, Mental Disorders, Retrospective Studies
Abstract

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E-06), PCDH7 (P = 2.0E-06), and IPO13 (P = 2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range [Formula: see text]: 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range [Formula: see text]: 0.46-0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

Published
2021

13. Diagnostic profiles among suicide decedents with and without borderline personality disorder.

Author

Kaufman, Erin A., Coon, Hilary, Shabalin, Andrey A., Monson, Eric T., Chen, Danli, Staley, Michael J., Keeshin, Brooks R., Docherty, Anna R., Bakian, Amanda V., and DiBlasi, Emily

Abstract

Background Borderline personality disorder (BPD) is a debilitating condition characterized by pervasive instability across multiple major domains of functioning. The majority of persons with BPD engage in self-injury and up to 10% die by suicide – rendering persons with this condition at exceptionally elevated risk of comorbidity and premature mortality. Better characterization of clinical risk factors among persons with BPD who die by suicide is urgently needed. Methods We examined patterns of medical and psychiatric diagnoses (1580 to 1700 Phecodes) among persons with BPD who died by suicide (n = 379) via a large suicide death data resource and biobank. In phenotype-based phenome-wide association tests, we compared these individuals to three other groups: (1) persons who died by suicide without a history of BPD (n = 9468), (2) persons still living with a history of BPD diagnosis (n = 280), and (3) persons who died by suicide with a different personality disorder (other PD n = 589). Results Multivariable logistic regression models revealed that persons with BPD who died by suicide were more likely to present with co-occurring psychiatric diagnoses, and have a documented history of self-harm in the medical system prior to death, relative to suicides without BPD. Posttraumatic stress disorder was more elevated among those with BPD who died by suicide relative to the other PD group. Conclusions We found significant differences among persons with BPD who died by suicide and all other comparison groups. Such differences may be clinically informative for identifying high-risk subtypes and providing targeted intervention approaches. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Cytokine gene polymorphisms and suicide risk in an Indian ancestral population: A case-control study.

Author

Kaushik, Ruchika, Nayak, Baibaswata, Patra, Bichitra Nanda, Docherty, Anna R., Shabalin, Andrey, and Behera, Chittaranjan

Subjects
SUICIDE risk factors, EVIDENCE gaps, SUICIDE, MEGALOPOLIS, INTERLEUKIN-6
Abstract

Background: India currently accounts for a majority of global suicide deaths. Research in European ancestry has established that suicide mortality has a significant genetic component, and suggests that inflammation may play a crucial role in the pathophysiology of suicide. Inflammation is also highly relevant in regions of increased pollution exposure, such as the megacities of India. To address the existing gaps in genetic research on suicide and possible association with inflammatory biomarkers, we examined genetic polymorphism and clinical risk phenotypes in a population-based suicide-death cohort, India. Material and methods: Genotyping of IL-1β(rs16944) & (rs1143627), IL-4(rs2070874), IL-6(rs1800795) and IL-10(rs1800896) was done in 234 post-mortem suicide-death cases and 256 post-mortem controls (N = 490) using PCR RFLP method. Results: Our analyses identified three significant (p < 0.001) associations of cytokine variants with suicide death, including IL-1β(rs16944), OR = 0.627; IL-4(rs2070874), OR = 0.524; and IL-6(rs1800795), OR = 2.509. Cases were more likely female and were more likely to have a history of psychiatric illness, though rate of psychiatric illness was low in suicide cases(9%). Conclusion: Our genetic results are generally consistent with previous research on risk for depression and suicidal behaviour, and both genetic and phenotypic results provide new insights into risk factors that may contribute to suicide in India. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author

Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F.M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T.F., Bigdeli, Tim B., Binder, Elisabeth B., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R.I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Hassan Kiadeh, Farnush Farhadi, Finucane, Hilary K., Foo, Jerome C., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E.J.C., Depaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Howard, David M., Ising, Marcus, Jansen, Rick, Jones, Ian, Jones, Lisa A., Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O’Reilly, Paul F., Oskarsson, Hogni, Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, Nöthen, Markus M., O’Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C.B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, der Auwera, Sandra Van, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Penninx, Brenda W.J.H., Perlis, Roy H., Porteous, David J., Potash, James B., Preisig, Martin, Rietschel, Marcella, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., O’Connell, Kevin S., Coombes, Brandon, Qiao, Zhen, Als, Thomas D., Børte, Sigrid, Charney, Alexander W., Drange, Ole Kristian, Gandal, Michael J., Hagenaars, Saskia P., Ikeda, Masashi, Kamitaki, Nolan, Kim, Minsoo, Krebs, Kristi, Panagiotaropoulou, Georgia, Schilder, Brian M., Sloofman, Laura G., Winsvold, Bendik S., Won, Hong-Hee, Abramova, Liliya, Adorjan, Kristina, Al Eissa, Mariam, Albani, Diego, Alliey-Rodriguez, Ney, Anjorin, Adebayo, Antilla, Verneri, Antoniou, Anastasia, Awasthi, Swapnil, Baek, Ji Hyun, Bass, Nicholas, Bauer, Michael, Beins, Eva C., Bergen, Sarah E., Birner, Armin, Bøen, Erlend, Boks, Marco P., Bosch, Rosa, Brum, Murielle, Brumpton, Ben M., Brunkhorst-Kanaan, Nathalie, Budde, Monika, Byerley, William, Cairns, Murray, Casas, Miquel, Cervantes, Pablo, Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Cunningham, Julie, Curtis, David, Czerski, Piotr M., Dale, Anders M., Dalkner, Nina, David, Friederike S., Djurovic, Srdjan, Dobbyn, Amanda L., Douzenis, Athanassios, Elvsåshagen, Torbjørn, Ferrier, I. Nicol, Fiorentino, Alessia, Foroud, Tatiana M., Forty, Liz, Frei, Oleksandr, Freimer, Nelson B., Frisén, Louise, Gade, Katrin, Garnham, Julie, Gelernter, Joel, Gizer, Ian R., Gordon-Smith, Katherine, Greenwood, Tiffany A., Guzman-Parra, José, Ha, Kyooseob, Haraldsson, Magnus, Hautzinger, Martin, Heilbronner, Urs, Hellgren, Dennis, Holmans, Peter A., Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S., Kalman, Janos L., Kamatani, Yoichiro, Kennedy, James L., Kittel-Schneider, Sarah, Kogevinas, Manolis, Koromina, Maria, Kranz, Thorsten M., Kranzler, Henry R., Kubo, Michiaki, Kupka, Ralph, Kushner, Steven A., Lavebratt, Catharina, Lawrence, Jacob, Leber, Markus, Lee, Heon-Jeong, Lee, Phil H., Levy, Shawn E., Lewis, Catrin, Liao, Calwing, Lundberg, Martin, Magnusson, Sigurdur H., Maihofer, Adam, Malaspina, Dolores, Maratou, Eirini, Martinsson, Lina, McGregor, Nathaniel W., McKay, James D., Medeiros, Helena, Millischer, Vincent, Moran, Jennifer L., Morris, Derek W., Mühleisen, Thomas W., O’Brien, Niamh, O’Donovan, Claire, Olde Loohuis, Loes M., Oruc, Lilijana, Papiol, Sergi, Pardiñas, Antonio F., Perry, Amy, Pfennig, Andrea, Porichi, Evgenia, Quested, Digby, Raj, Towfique, Rapaport, Mark H., DePaulo, J. Raymond, Regeer, Eline J., Rivas, Fabio, Roth, Julian, Roussos, Panos, Ruderfer, Douglas M., Sánchez-Mora, Cristina, Senner, Fanny, Sharp, Sally, Shilling, Paul D., Sirignano, Lea, Slaney, Claire, Smeland, Olav B., Sobell, Janet L., Artigas, Maria Soler, Spijker, Anne T., Stein, Dan J., Strauss, John S., Świątkowska, Beata, Terao, Chikashi, Toma, Claudio, Tooney, Paul, Tsermpini, Evangelia-Eirini, Vawter, Marquis P., Vedder, Helmut, Walters, James T.R., Xi, Simon, Xu, Wei, Kay Yang, Jessica Mei, Young, Allan H., Young, Hannah, Zandi, Peter P., Zhou, Hang, Zillich, Lea, HUNT All-In Psychiatry, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Alfredsson, Lars, Babadjanova, Gulja, Backlund, Lena, Bellivier, Frank, Bengesser, Susanne, Berrettini, Wade H., Blackwood, Douglas H.R., Boehnke, Michael, Carr, Vaughan J., Catts, Stanley, Corvin, Aiden, Craddock, Nicholas, Dikeos, Dimitris, Etain, Bruno, Ferentinos, Panagiotis, Frye, Mark, Fullerton, Janice M., Gawlik, Micha, Gershon, Elliot S., Green, Melissa J., Grigoroiu-Serbanescu, Maria, Hauser, Joanna, Henskens, Frans, Hillert, Jan, Hong, Kyung Sue, Hultman, Christina M., Hveem, Kristian, Iwata, Nakao, Jablensky, Assen V., Kahn, René S., Kelsoe, John R., Kirov, George, Landén, Mikael, Leboyer, Marion, Lissowska, Jolanta, Lochner, Christine, Loughland, Carmel, Mathews, Carol A., Mayoral, Fermin, McElroy, Susan L., McMahon, Francis J., Melle, Ingrid, Michie, Patricia, Mitchell, Philip B., Morken, Gunnar, Mowry, Bryan, Myers, Richard M., Neale, Benjamin M., Nievergelt, Caroline M., Oedegaard, Ketil J., Olsson, Tomas, Pantelis, Chris, Pato, Carlos, Pato, Michele T., Patrinos, George P., Ramos-Quiroga, Josep Antoni, Reif, Andreas, Reininghaus, Eva Z., Ribasés, Marta, Rouleau, Guy A., Saito, Takeo, Schall, Ulrich, Schalling, Martin, Schofield, Peter R., Scott, Laura J., Scott, Rodney J., Serretti, Alessandro, Weickert, Cynthia Shannon, Stordal, Eystein, Turecki, Gustavo, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Waldman, Irwin D., Weickert, Thomas W., Zwart, John-Anker, Biernacka, Joanna M., Nurnberger, John I., Edenberg, Howard J., Stahl, Eli A., McQuillin, Andrew, Di Florio, Arianna, Ophoff, Roel A., Andreassen, Ole A., Adan, Roger A.H., Ando, Tetsuya, Aschauer, Harald, Baker, Jessica H., Bencko, Vladimir, Bergen, Andrew W., Birgegård, Andreas, Boden, Joseph M., Boehm, Ilka, Boni, Claudette, Perica, Vesna Boraska, Brandt, Harry, Buehren, Katharina, Bulik, Cynthia M., Burghardt, Roland, Carlberg, Laura, Cassina, Matteo, Clementi, Maurizio, Cone, Roger D., Courtet, Philippe, Crawford, Steven, Crow, Scott, Crowley, James J., Danner, Unna N., Davis, Oliver S.P., de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece E., Dick, Danielle M., Dina, Christian, Dmitrzak-Weglarz, Monika, Martinez, Elisa Docampo, Duncan, Laramie E., Egberts, Karin, Marshall, Christian R., Mattingsdal, Morten, McDevitt, Sara, Meulenbelt, Ingrid, Micali, Nadia, Mitchell, James, Mitchell, Karen, Monteleone, Palmiero, Monteleone, Alessio Maria, Munn-Chernoff, Melissa A., Nacmias, Benedetta, Navratilova, Marie, Ntalla, Ioanna, Olsen, Catherine M., O’Toole, Julie K., Padyukov, Leonid, Palotie, Aarno, Pantel, Jacques, Papezova, Hana, Parker, Richard, Pearson, John F., Ehrlich, Stefan, Escaramís, Geòrgia, Espeseth, Thomas, Estivill, Xavier, Farmer, Anne, Favaro, Angela, Fernández-Aranda, Fernando, Fichter, Manfred M., Fischer, Krista, Floyd, James A.B., Föcker, Manuel, Foretova, Lenka, Forzan, Monica, Franklin, Christopher S., Gallinger, Steven, Gambaro, Giovanni, Giegling, Ina, Giuranna, Johanna, Giusti-Rodríquez, Paola, Gonidakis, Fragiskos, Gordon, Scott, Gorwood, Philip, Mayora, Monica Gratacos, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Halmi, Katherine A., Hanscombe, Ken B., Hatzikotoulas, Konstantinos, Hebebrand, Johannes, Helder, Sietske G., Henders, Anjali K., Herpertz-Dahlmann, Beate, Herzog, Wolfgang, Hinney, Anke, Horwood, L. John, Hübel, Christopher, Petersen, Liselotte V., Pinto, Dalila, Purves, Kirstin L., Raevuori, Anu, Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Ricca, Valdo, Ripatti, Samuli, Ritschel, Franziska, Roberts, Marion, Rujescu, Dan, Rybakowski, Filip, Santonastaso, Paolo, Scherag, André, Scherer, Stephen W., Schmidt, Ulrike, Schork, Nicholas J., Schosser, Alexandra, Seitz, Jochen, Slachtova, Lenka, Slagboom, P. Eline, Slof-Op ‘t Landt, Margarita C.T., Slopien, Agnieszka, Soranzo, Nicole, Sorbi, Sandro, Southam, Lorraine, Steen, Vidar W., Strober, Michael, Huckins, Laura M., Hudson, James I., Imgart, Hartmut, Inoko, Hidetoshi, Janout, Vladimir, Jiménez-Murcia, Susana, Johnson, Craig, Jordan, Jennifer, Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Kaplan, Allan S., Kaprio, Jaakko, Karhunen, Leila, Karwautz, Andreas, Kas, Martien J.H., Kaye, Walter H., Kennedy, Martin A., Keski-Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl-Ri, Kirk, Katherine M., Klareskog, Lars, Klump, Kelly L., Knudsen, Gun Peggy S., Larsen, Janne T., Le Hellard, Stephanie, Leppä, Virpi M., Li, Dong, Lichtenstein, Paul, Lilenfeld, Lisa, Lin, Bochao Danae, Lundervold, Astri, Luykx, Jurjen, Magistretti, Pierre J., Maj, Mario, Mannik, Katrin, Marsal, Sara, Stuber, Garret D., Szatkiewicz, Jin P., Tachmazidou, Ioanna, Tenconi, Elena, Thornton, Laura M., Tortorella, Alfonso, Tozzi, Federica, Treasure, Janet, Tsitsika, Artemis, Tyszkiewicz-Nwafor, Marta, Tziouvas, Konstantinos, van Elburg, Annemarie A., van Furth, Eric F., Wade, Tracey D., Wagner, Gudrun, Walton, Esther, Watson, Hunna J., Whiteman, David C., Wichmann, H. Erich, Widen, Elisabeth, Woodside, D. Blake, Yao, Shuyang, Yilmaz, Zeynep, Zeggini, Eleftheria, Zerwas, Stephanie, Zipfel, Stephan, Jungkunz, Martin, Dietl, Lydie, Schwarze, Cornelia E., Dahmen, Norbert, Schott, Björn H., Mobascher, Arian, Lieb, Klaus, Roepke, Stefan, Schmahl, Christian, Bohus, Martin, Crivelli, Silvia, Dennis, Michelle F., Harvey, Phillip D., Carter, Bruce W., Huffman, Jennifer E., Jacobson, Daniel, Madduri, Ravi, Olsen, Maren K., Pestian, John, Gaziano, J. Michael, Muralidhar, Sumitra, Ramoni, Rachel, Beckham, Jean, Chang, Kyong-Mi, O’Donnell, Christopher J., Tsao, Philip S., Breeling, James, Huang, Grant, Romero, J.P. Casas, Moser, Jennifer, Whitbourne, Stacey B., Brewer, Jessica V., Aslan, Mihaela, Connor, Todd, Argyres, Dean P., Stephens, Brady, Brophy, Mary T., Humphries, Donald E., Selva, Luis E., Do, Nhan, Shayan, Shahpoor, Cho, Kelly, Pyarajan, Saiju, Hauser, Elizabeth, Sun, Yan, Zhao, Hongyu, Wilson, Peter, McArdle, Rachel, Dellitalia, Louis, Mattocks, Kristin, Harley, John, Zablocki, Clement J., Whittle, Jeffrey, Jacono, Frank, Gutierrez, Salvador, Gibson, Gretchen, Hammer, Kimberly, Kaminsky, Laurence, Villareal, Gerardo, Kinlay, Scott, Xu, Junzhe, Hamner, Mark, Mathew, Roy, Bhushan, Sujata, Iruvanti, Pran, Godschalk, Michael, Ballas, Zuhair, Ivins, Douglas, Mastorides, Stephen, Moorman, Jonathan, Gappy, Saib, Klein, Jon, Ratcliffe, Nora, Florez, Hermes, Okusaga, Olaoluwa, Murdoch, Maureen, Sriram, Peruvemba, Yeh, Shing Shing, Tandon, Neeraj, Jhala, Darshana, Aguayo, Samuel, Cohen, David, Sharma, Satish, Liangpunsakul, Suthat, Oursler, Kris Ann, Whooley, Mary, Ahuja, Sunil, Constans, Joseph, Meyer, Paul, Greco, Jennifer, Rauchman, Michael, Servatius, Richard, Gaddy, Melinda, Wallbom, Agnes, Morgan, Timothy, Stapley, Todd, Sherman, Scott, Ross, George, Tsao, Philip, Strollo, Patrick, Jr., Boyko, Edward, Meyer, Laurence, Gupta, Samir, Huq, Mostaqul, Fayad, Joseph, Hung, Adriana, Lichy, Jack, Hurley, Robin, Robey, Brooks, Striker, Robert, Kang, JooEun, Campos, Adrian I., Edwards, Alexis C., Galfalvy, Hanga, Levey, Daniel F., Lori, Adriana, Shabalin, Andrey, Starnawska, Anna, Su, Mei-Hsin, Adams, Mark, Gandal, Michael, Hafferty, Jonathan D., Hishimoto, Akitoyo, Okazaki, Satoshi, Otsuka, Ikuo, Ware, Erin B., Chang, Xiao, Chen, Wei J., Chen, Hsi-Chung, DiBlasi, Emily, Duriez, Philibert, Glatt, Stephen J., Hwu, Hai-Gwo, Jain, Sonia, Keel, Pamela K., Liao, Shih-Cheng, Liu, Chih-Min, Mitchell, James E., Monson, Eric T., Powers, Abigail, Rozanov, Vsevolod, Sokolowski, Marcus, Tsuang, Ming T., Appadurai, Vivek, Soler Artigas, María, Van der Auwera, Sandra, Azevedo, M. Helena, Bau, Claiton H.D., Braff, David L., Bryant, Richard, Cahn, Wiepke, Casas, Miguel, Cervilla, Jorge A., Chaumette, Boris, Craig, David, Fanous, Ayman H., Gatt, Justine M., Gejman, Pablo V., Grevet, Eugenio H., Gutierrez, Blanca, Guzman-Parra, Jose, Hamshere, Marian L., Hartmann, Annette, Heilmann-Heimbach, Stefanie, Jonsson, Lina, Koenen, Karestan C., Konte, Bettina, Krebs, Marie-Odile, Molina, Esther, Nievergelt, Caroline, Nimgaonkar, Vishwajit, Pimm, Jonathan, Power, Robert A., Richarte, Vanesa, Roberts, Andrea, Roberts, Gloria, Rovaris, Diego L., Sanders, Alan R., Sklar, Pamela, Sonuga-Barke, Edmund J.S., Spalletta, Gianfranco, Vilar-Ribó, Laura, Shannon Weickert, Cynthia, Williams, Leanne M., Zai, Clement C., Ashley-Koch, Allison E., Beckham, Jean C., Hauser, Elizabeth R., Hauser, Michael A., Kimbrel, Nathan A., Lindquist, Jennifer H., McMahon, Benjamin, Oslin, David W., Qin, Xuejun, Erlangsen, Annette, Kessler, Ronald C., Porteous, David, Ursano, Robert J., Wasserman, Danuta, Coon, Hilary, Demontis, Ditte, Docherty, Anna R., Kuo, Po-Hsiu, Mann, J. John, Rentería, Miguel E., Stein, Murray B., and Willour, Virginia

Published
2022
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16. The benefit of diagnostic whole genome sequencing in schizophrenia and other psychotic disorders

Author

Alkelai, Anna, Greenbaum, Lior, Docherty, Anna R., Shabalin, Andrey A., Povysil, Gundula, Malakar, Ayan, Hughes, Daniel, Delaney, Shannon L., Peabody, Emma P., McNamara, James, Gelfman, Sahar, Baugh, Evan H., Zoghbi, Anthony W., Harms, Matthew B., Hwang, Hann-Shyan, Grossman-Jonish, Anat, Aggarwal, Vimla, Heinzen, Erin L., Jobanputra, Vaidehi, Pulver, Ann E., Lerer, Bernard, and Goldstein, David B.

Published
2022
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17. Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative.

Author

Docherty, Anna R, Fonseca-Pedrero, Eduardo, Debbané, Martin, Chan, Raymond CK, Linscott, Richard J, Jonas, Katherine G, Cicero, David C, Green, Melissa J, Simms, Leonard J, Mason, Oliver, Watson, David, Ettinger, Ulrich, Waszczuk, Monika, Rapp, Alexander, Grant, Phillip, Kotov, Roman, DeYoung, Colin G, Ruggero, Camilo J, Eaton, Nicolas R, Krueger, Robert F, Patrick, Christopher, Hopwood, Christopher, O’Neill, F Anthony, Zald, David H, Conway, Christopher C, Adkins, Daniel E, Waldman, Irwin D, van Os, Jim, Sullivan, Patrick F, Anderson, John S, Shabalin, Andrey A, Sponheim, Scott R, Taylor, Stephan F, Grazioplene, Rachel G, Bacanu, Silviu A, Bigdeli, Tim B, Haenschel, Corinna, Malaspina, Dolores, Gooding, Diane C, Nicodemus, Kristin, Schultze-Lutter, Frauke, Barrantes-Vidal, Neus, Mohr, Christine, Carpenter, William T, and Cohen, Alex S

Subjects
Brain Disorders, Human Genome, Genetics, Mental Health, Good Health and Well Being, Datasets as Topic, Humans, Information Dissemination, Intersectoral Collaboration, Models, Theoretical, Psychotic Disorders, Schizophrenia, Schizotypal Personality Disorder, data sharing, schizotypy, schizotypal, psychos is, schizophrenia, phenotype, genetic, ICSR, HiTOP, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

Published
2018

20. Absence of nonfatal suicidal behavior preceding suicide death reveals differences in clinical risks

Author

Coon, Hilary, primary, Shabalin, Andrey, additional, DiBlasi, Emily, additional, Monson, Eric T., additional, Han, Seonggyun, additional, Kaufman, Erin A., additional, Chen, Danli, additional, Kious, Brent, additional, Molina, Nicolette, additional, Yu, Zhe, additional, Staley, Michael, additional, Crockett, David K., additional, Colbert, Sarah M., additional, Mullins, Niamh, additional, Bakian, Amanda V., additional, Docherty, Anna R., additional, and Keeshin, Brooks, additional

Published
2024
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21. Estimation of Interpretable eQTL Effect Sizes Using a Log of Linear Model

Author

Palowitch, John, Shabalin, Andrey, Zhou, Yihui, Nobel, Andrew B., and Wright, Fred A.

Subjects
Statistics - Methodology
Abstract

The study of expression Quantitative Trait Loci (eQTL) is an important problem in genomics and biomedicine. While detection (testing) of eQTL associations has been widely studied, less work has been devoted to the estimation of eQTL effect size. To reduce false positives, detection methods frequently rely on linear modeling of rank-based normalized or log-transformed gene expression data. Unfortunately, these approaches do not correspond to the simplest model of eQTL action, and thus yield estimates of eQTL association that can be uninterpretable and inaccurate. In this paper we propose a new, log-of-linear model for eQTL action, termed ACME, that captures allelic contributions to cis-acting eQTLs in an additive fashion, yielding effect size estimates that correspond to a biologically coherent model of cis-eQTLs. We describe a non-linear least-squares algorithm to fit the model by maximum likelihood, and obtain corresponding $p$-values. We perform careful investigation of the model using a combination of simulated data and data from the Genotype Tissue Expression (GTEx) project. Our results reveal little evidence for dominance effects, a parsimonious result that accords with a simple biological model for allele-specific expression and supports use of the ACME model. We show that Type-I error is well-controlled under our approach in a realistic setting, so that rank-based normalizations are unnecessary. Furthermore, we show that such normalizations can be detrimental to power and estimation accuracy under the proposed model. We then provide summaries of ACME effect sizes for whole-genome cis-eQTLs in the GTEx data.

Published
2016

22. Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis

Author

Yang, Fan, Wang, Jiebiao, Consortium, The GTEx, Pierce, Brandon L, Chen, Lin S, Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Im, Hae Kyung, Jo, Brian, Kang, Eun Yong, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, and Wang, Gao

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Selection, Genetic, Tissue Distribution, GTEx Consortium, Medical and Health Sciences, Bioinformatics
Abstract

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes (cis-eQTLs). More research is needed to identify effects of genetic variation on distant genes (trans-eQTLs) and understand their biological mechanisms. One common trans-eQTLs mechanism is "mediation" by a local (cis) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are "cis-mediators" of trans-eQTLs, including those "cis-hubs" involved in regulation of many trans-genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans-eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis-mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis-hubs and trans-eQTL regulation across tissue types.

Published
2017

23. Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Author

Saha, Ashis, Kim, Yungil, Gewirtz, Ariel DH, Jo, Brian, Gao, Chuan, McDowell, Ian C, Consortium, The GTEx, Engelhardt, Barbara E, Battle, Alexis, Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Im, Hae Kyung, Kang, Eun Yong, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, and Sul, Jae Hoon

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Bayes Theorem, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genotyping Techniques, Humans, Organ Specificity, Polymorphism, Single Nucleotide, RNA Splicing, Sequence Analysis, RNA, GTEx Consortium, Medical and Health Sciences, Bioinformatics
Abstract

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.

Published
2017

24. Dynamic landscape and regulation of RNA editing in mammals

Author

Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A, Xi, Hualin S, Yeger-Lotem, Esti, and Zappala, Zachary

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Adenosine Deaminase, Animals, Female, Genotype, HEK293 Cells, Humans, Male, Mice, Muscles, Nuclear Proteins, Organ Specificity, Primates, Proteolysis, RNA Editing, RNA-Binding Proteins, Spatio-Temporal Analysis, Species Specificity, Transcriptome, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, General Science & Technology
Abstract

Adenosine-to-inosine (A-to-I) RNA editing is a conserved post-transcriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules. Although many editing sites have recently been discovered, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of non-repetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis- and trans-regulation of A-to-I editing.

Published
2017

25. Landscape of X chromosome inactivation across human tissues

Author

Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A, Xi, Hualin S, Yeger-Lotem, Esti, and Zappala, Zachary

Subjects
Genetics, Clinical Research, Human Genome, Generic health relevance, Good Health and Well Being, Chromosomes, Human, X, Female, Genes, X-Linked, Genome, Human, Genomics, Humans, Male, Organ Specificity, Phenotype, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome, X Chromosome Inactivation, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, General Science & Technology
Abstract

X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals. The extent to which XCI is shared between cells and tissues remains poorly characterized, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression and phenotypic traits. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.

Published
2017

26. The impact of rare variation on gene expression across tissues

Author

Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A, Xi, Hualin S, Yeger-Lotem, Esti, and Zappala, Zachary

Subjects
Bayes Theorem, Female, Gene Expression Profiling, Genetic Variation, Genome, Human, Genomics, Genotype, Humans, Male, Models, Genetic, Organ Specificity, Sequence Analysis, RNA, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, General Science & Technology
Abstract

Rare genetic variants are abundant in humans and are expected to contribute to individual disease risk. While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants. Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles, but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues, but their effects across tissues are unknown. Here we identify gene expression outliers, or individuals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release. We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes.

Published
2017

27. Genetic effects on gene expression across human tissues

Author

Aguet, François, Brown, Andrew A, Castel, Stephane E, Davis, Joe R, He, Yuan, Jo, Brian, Mohammadi, Pejman, Park, YoSon, Parsana, Princy, Segrè, Ayellet V, Strober, Benjamin J, Zappala, Zachary, Cummings, Beryl B, Gelfand, Ellen T, Hadley, Kane, Huang, Katherine H, Lek, Monkol, Li, Xiao, Nedzel, Jared L, Nguyen, Duyen Y, Noble, Michael S, Sullivan, Timothy J, Tukiainen, Taru, MacArthur, Daniel G, Getz, Gad, Addington, Anjene, Guan, Ping, Koester, Susan, Little, A Roger, Lockhart, Nicole C, Moore, Helen M, Rao, Abhi, Struewing, Jeffery P, Volpi, Simona, Brigham, Lori E, Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F, Lonsdale, John T, McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Bryan, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A, Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A, Gillard, Bryan M, Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T, Jewell, Scott D, Montroy, Robert G, Rohrer, Daniel C, Valley, Dana, Mash, Deborah C, Davis, David A, Sobin, Leslie, Barcus, Mary E, Branton, Philip A, Abell, Nathan S, Balliu, Brunilda, Delaneau, Olivier, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Han, Buhm, He, Amy Z, Hormozdiari, Farhad, Li, Xin, Liu, Boxiang, Kang, Eun Yong, McDowell, Ian C, Ongen, Halit, Palowitch, John J, Peterson, Christine B, Quon, Gerald, Ripke, Stephan, Saha, Ashis, Shabalin, Andrey A, Shimko, Tyler C, Sul, Jae Hoon, Teran, Nicole A, Tsang, Emily K, Zhang, Hailei, Zhou, Yi-Hui, Bustamante, Carlos D, Cox, Nancy J, and Guigó, Roderic

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Biotechnology, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Generic health relevance, Alleles, Chromosomes, Human, Disease, Female, Gene Expression Profiling, Gene Expression Regulation, Genetic Variation, Genome, Human, Genotype, Humans, Male, Organ Specificity, Quantitative Trait Loci, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, Lead analysts:, Laboratory, Data Analysis &Coordinating Center (LDACC):, NIH program management:, Biospecimen collection:, Pathology:, eQTL manuscript working group:, General Science & Technology
Abstract

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

Published
2017

29. Genome-wide significant regions in 43 Utah high-risk families implicate multiple genes involved in risk for completed suicide

Author

Coon, Hilary, Darlington, Todd M., DiBlasi, Emily, Callor, W. Brandon, Ferris, Elliott, Fraser, Alison, Yu, Zhe, William, Nancy, Das, Sujan C., Crowell, Sheila E., Chen, Danli, Anderson, John S., Klein, Michael, Jerominski, Leslie, Cannon, Dale, Shabalin, Andrey, Docherty, Anna, Williams, Megan, Smith, Ken R., Keeshin, Brooks, Bakian, Amanda V., Christensen, Erik, Li, Qingqin S., Camp, Nicola J., and Gray, Douglas

Published
2020
Full Text
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30. A methylation study of long-term depression risk

Author

Clark, Shaunna L., Hattab, Mohammad W., Chan, Robin F., Shabalin, Andrey A., Han, Laura K. M., Zhao, Min, Smit, Johannes H., Jansen, Rick, Milaneschi, Yuri, Xie, Lin Ying, van Grootheest, Gerard, Penninx, Brenda W. J. H., Aberg, Karolina A., and van den Oord, Edwin J. C. G.

Published
2020
Full Text
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32. An integrated map of structural variation in 2,504 human genomes.

Author

Sudmant, Peter H, Rausch, Tobias, Gardner, Eugene J, Handsaker, Robert E, Abyzov, Alexej, Huddleston, John, Zhang, Yan, Ye, Kai, Jun, Goo, Fritz, Markus Hsi-Yang, Konkel, Miriam K, Malhotra, Ankit, Stütz, Adrian M, Shi, Xinghua, Casale, Francesco Paolo, Chen, Jieming, Hormozdiari, Fereydoun, Dayama, Gargi, Chen, Ken, Malig, Maika, Chaisson, Mark JP, Walter, Klaudia, Meiers, Sascha, Kashin, Seva, Garrison, Erik, Auton, Adam, Lam, Hugo YK, Mu, Xinmeng Jasmine, Alkan, Can, Antaki, Danny, Bae, Taejeong, Cerveira, Eliza, Chines, Peter, Chong, Zechen, Clarke, Laura, Dal, Elif, Ding, Li, Emery, Sarah, Fan, Xian, Gujral, Madhusudan, Kahveci, Fatma, Kidd, Jeffrey M, Kong, Yu, Lameijer, Eric-Wubbo, McCarthy, Shane, Flicek, Paul, Gibbs, Richard A, Marth, Gabor, Mason, Christopher E, Menelaou, Androniki, Muzny, Donna M, Nelson, Bradley J, Noor, Amina, Parrish, Nicholas F, Pendleton, Matthew, Quitadamo, Andrew, Raeder, Benjamin, Schadt, Eric E, Romanovitch, Mallory, Schlattl, Andreas, Sebra, Robert, Shabalin, Andrey A, Untergasser, Andreas, Walker, Jerilyn A, Wang, Min, Yu, Fuli, Zhang, Chengsheng, Zhang, Jing, Zheng-Bradley, Xiangqun, Zhou, Wanding, Zichner, Thomas, Sebat, Jonathan, Batzer, Mark A, McCarroll, Steven A, 1000 Genomes Project Consortium, Mills, Ryan E, Gerstein, Mark B, Bashir, Ali, Stegle, Oliver, Devine, Scott E, Lee, Charles, Eichler, Evan E, and Korbel, Jan O

Subjects
Genomes Project Consortium, Humans, Genetic Predisposition to Disease, Physical Chromosome Mapping, Sequence Analysis, DNA, Genetics, Medical, Genetics, Population, Genomics, Sequence Deletion, Amino Acid Sequence, Genotype, Haplotypes, Homozygote, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome, Human, Molecular Sequence Data, Genetic Variation, Genome-Wide Association Study, Mutation Rate, Sequence Analysis, DNA, Genetics, Medical, Population, Polymorphism, Single Nucleotide, Genome, Human, General Science & Technology
Abstract

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Published
2015

33. An Empirical Bayes Approach for Multiple Tissue eQTL Analysis

Author

Li, Gen, Shabalin, Andrey A., Rusyn, Ivan, Wright, Fred A., and Nobel, Andrew B.

Subjects
Statistics - Methodology
Abstract

Expression quantitative trait loci (eQTL) analyses, which identify genetic markers associated with the expression of a gene, are an important tool in the understanding of diseases in human and other populations. While most eQTL studies to date consider the connection between genetic variation and expression in a single tissue, complex, multi-tissue data sets are now being generated by the GTEx initiative. These data sets have the potential to improve the findings of single tissue analyses by borrowing strength across tissues, and the potential to elucidate the genotypic basis of differences between tissues. In this paper we introduce and study a multivariate hierarchical Bayesian model (MT-eQTL) for multi-tissue eQTL analysis. MT-eQTL directly models the vector of correlations between expression and genotype across tissues. It explicitly captures patterns of variation in the presence or absence of eQTLs, as well as the heterogeneity of effect sizes across tissues. Moreover, the model is applicable to complex designs in which the set of donors can (i) vary from tissue to tissue, and (ii) exhibit incomplete overlap between tissues. The MT-eQTL model is marginally consistent, in the sense that the model for a subset of tissues can be obtained from the full model via marginalization. Fitting of the MT-eQTL model is carried out via empirical Bayes, using an approximate EM algorithm. Inferences concerning eQTL detection and the configuration of eQTLs across tissues are derived from adaptive thresholding of local false discovery rates, and maximum a-posteriori estimation, respectively. We investigate the MT-eQTL model through a simulation study, and rigorously establish the FDR control of the local FDR testing procedure under mild assumptions appropriate for dependent data., Comment: accepted by Biostatistics

Published
2013

35. Matrix eQTL: Ultra fast eQTL analysis via large matrix operations

Author

Shabalin, Andrey A.

Subjects
Quantitative Biology - Genomics
Abstract

Expression quantitative trait loci (eQTL) mapping aims to determine genomic regions that regulate gene transcription. Expression QTL is used to study the regulatory structure of normal tissues and to search for genetic factors in complex diseases such as cancer, diabetes, and cystic fibrosis. A modern eQTL dataset contains millions of SNPs and thousands of transcripts measured for hundreds of samples. This makes the analysis computationally complex as it involves independent testing for association for every transcript-SNP pair. The heavy computational burden makes eQTL analysis less popular, often forces analysts to restrict their attention to just a subset of transcripts and SNPs. As larger genotype and gene expression datasets become available, the demand for fast tools for eQTL analysis increases. We present a new method for fast eQTL analysis via linear models, called Matrix eQTL. Matrix eQTL can model and test for association using both linear regression and ANOVA models. The models can include covariates to account for such factors as population structure, gender, and clinical variables. It also supports testing of heteroscedastic models and models with correlated errors. In our experiment on large datasets Matrix eQTL was thousands of times faster than the existing popular software for QTL/eQTL analysis. Matrix eQTL is implemented as both Matlab and R packages and thus can easily be run on Windows, Mac OS, and Linux systems. The software is freely available at the following address: http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL, Comment: 9 pages, 1 figure

Published
2011

36. Reconstruction of a Low-rank Matrix in the Presence of Gaussian Noise

Author

Shabalin, Andrey and Nobel, Andrew

Subjects
Statistics - Methodology, Mathematics - Statistics Theory
Abstract

In this paper we study the problem of reconstruction of a low-rank matrix observed with additive Gaussian noise. First we show that under mild assumptions (about the prior distribution of the signal matrix) we can restrict our attention to reconstruction methods that are based on the singular value decomposition of the observed matrix and act only on its singular values (preserving the singular vectors). Then we determine the effect of noise on the SVD of low-rank matrices by building a connection between matrix reconstruction problem and spiked population model in random matrix theory. Based on this knowledge, we propose a new reconstruction method, called RMT, that is designed to reverse the effect of the noise on the singular values of the signal matrix and adjust for its effect on the singular vectors. With an extensive simulation study we show that the proposed method outperform even oracle versions of both soft and hard thresholding methods and closely matches the performance of a general oracle scheme., Comment: 34 pages, 7 figures

Published
2010

37. Finding large average submatrices in high dimensional data

Author

Shabalin, Andrey A., Weigman, Victor J., Perou, Charles M., and Nobel, Andrew B.

Subjects
Quantitative Biology - Genomics, Quantitative Biology - Quantitative Methods
Abstract

The search for sample-variable associations is an important problem in the exploratory analysis of high dimensional data. Biclustering methods search for sample-variable associations in the form of distinguished submatrices of the data matrix. (The rows and columns of a submatrix need not be contiguous.) In this paper we propose and evaluate a statistically motivated biclustering procedure (LAS) that finds large average submatrices within a given real-valued data matrix. The procedure operates in an iterative-residual fashion, and is driven by a Bonferroni-based significance score that effectively trades off between submatrix size and average value. We examine the performance and potential utility of LAS, and compare it with a number of existing methods, through an extensive three-part validation study using two gene expression datasets. The validation study examines quantitative properties of biclusters, biological and clinical assessments using auxiliary information, and classification of disease subtypes using bicluster membership. In addition, we carry out a simulation study to assess the effectiveness and noise sensitivity of the LAS search procedure. These results suggest that LAS is an effective exploratory tool for the discovery of biologically relevant structures in high dimensional data. Software is available at https://genome.unc.edu/las/., Comment: Published in at http://dx.doi.org/10.1214/09-AOAS239 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Published
2009
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38. Heritability and genomics of gene expression in peripheral blood

Author

Wright, Fred A, Sullivan, Patrick F, Brooks, Andrew I, Zou, Fei, Sun, Wei, Xia, Kai, Madar, Vered, Jansen, Rick, Chung, Wonil, Zhou, Yi-Hui, Abdellaoui, Abdel, Batista, Sandra, Butler, Casey, Chen, Guanhua, Chen, Ting-Huei, D'Ambrosio, David, Gallins, Paul, Ha, Min Jin, Hottenga, Jouke Jan, Huang, Shunping, Kattenberg, Mathijs, Kochar, Jaspreet, Middeldorp, Christel M, Qu, Ani, Shabalin, Andrey, Tischfield, Jay, Todd, Laura, Tzeng, Jung-Ying, van Grootheest, Gerard, Vink, Jacqueline M, Wang, Qi, Wang, Wei, Wang, Weibo, Willemsen, Gonneke, Smit, Johannes H, de Geus, Eco J, Yin, Zhaoyu, Penninx, Brenda WJH, and Boomsma, Dorret I

Subjects
Biotechnology, Human Genome, Genetics, Blood, Gene Expression Profiling, Gene Expression Regulation, Genotype, Humans, Inheritance Patterns, Likelihood Functions, Netherlands, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

We assessed gene expression profiles in 2,752 twins, using a classic twin design to quantify expression heritability and quantitative trait loci (eQTLs) in peripheral blood. The most highly heritable genes (∼777) were grouped into distinct expression clusters, enriched in gene-poor regions, associated with specific gene function or ontology classes, and strongly associated with disease designation. The design enabled a comparison of twin-based heritability to estimates based on dizygotic identity-by-descent sharing and distant genetic relatedness. Consideration of sampling variation suggests that previous heritability estimates have been upwardly biased. Genotyping of 2,494 twins enabled powerful identification of eQTLs, which we further examined in a replication set of 1,895 unrelated subjects. A large number of non-redundant local eQTLs (6,756) met replication criteria, whereas a relatively small number of distant eQTLs (165) met quality control and replication standards. Our results provide a new resource toward understanding the genetic control of transcription.

Published
2014

41. Prototype Model of Autonomous Offshore Drilling Complex

Author

Lupuleac, Sergey, Toropov, Evgeny, Shabalin, Andrey, Kirillov, Mikhail, Bock, Hans Georg, Series Editor, de Hoog, Frank, Series Editor, Friedman, Avner, Series Editor, Gupta, Arvind, Series Editor, Nachbin, André, Series Editor, Ozawa, Tohru, Series Editor, Pulleyblank, William R., Series Editor, Rusten, Torgeir, Series Editor, Santosa, Fadil, Series Editor, Seo, Jin Keun, Series Editor, Tornberg, Anna-Karin, Series Editor, Quintela, Peregrina, editor, Barral, Patricia, editor, Gómez, Dolores, editor, Pena, Francisco J., editor, Rodríguez, Jerónimo, editor, Salgado, Pilar, editor, and Vázquez-Méndez, Miguel E., editor

Published
2017
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44. Deep Sequencing of Three Loci Implicated in Large-Scale Genome-Wide Association Study Smoking Meta-Analyses

Author

Clark, Shaunna L., McClay, Joseph L., Adkins, Daniel E., Aberg, Karolina A., Kumar, Gaurav, Nerella, Sri, Xie, Linying, Collins, Ann L., Crowley, James J., Quakenbush, Corey R., Hillard, Christopher E., Gao, Guimin, Shabalin, Andrey A., Peterson, Roseann E., Copeland, William E., Silberg, Judy L., Maes, Hermine, Sullivan, Patrick F., Costello, Elizabeth J., and van den Oord, Edwin J.

Published
2016

45. GWAS Meta-Analysis of Suicide Attempt:Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

Author

Docherty, Anna R., Mullins, Niamh, Ashley-Koch, Allison E., Qin, Xuejun, Coleman, Jonathan R.I., Shabalin, Andrey, Kang, Joo Eun, Murnyak, Balasz, Wendt, Frank, Adams, Mark, Campos, Adrian I., DiBlasi, Emily, Fullerton, Janice M., Kranzler, Henry R., Bakian, Amanda V., Monson, Eric T., Rentería, Miguel E., Walss-Bass, Consuelo, Andreassen, Ole A., Behera, Chittaranjan, Bulik, Cynthia M., Edenberg, Howard J., Kessler, Ronald C., John Mann, J., Nurnberger, John I., Pistis, Giorgio, Streit, Fabian, Ursano, Robert J., Polimanti, Renato, Dennis, Michelle, Garrett, Melanie, Hair, Lauren, Harvey, Philip, Hauser, Elizabeth R., Hauser, Michael A., Huffman, Jennifer, Jacobson, Daniel, Madduri, Ravi, McMahon, Benjamin, Oslin, David W., Trafton, Jodie, Awasthi, Swapnil, Berrettini, Wade H., Bohus, Martin, Chang, Xiao, Chen, Hsi Chung, Chen, Wei J., Christensen, Erik D.M.D., Crow, Scott, Duriez, Philibert, Edwards, Alexis C., Fernández-Aranda, Fernando, Galfalvy, Hanga, Gandal, Michael, Gorwood, Philip, Guo, Yiran, Hafferty, Jonathan D., Hakonarson, Hakon, Halmi, Katherine A., Hishimoto, Akitoyo, Jain, Sonia, Jamain, Stéphane, Jiménez-Murcia, Susana, Johnson, Craig, Kaplan, Allan S., Kaye, Walter H., Keel, Pamela K., Kennedy, James L., Kim, Minsoo, Klump, Kelly L., Levey, Daniel F., Li, Dong, Liao, Shih Cheng, Lieb, Klaus, Lilenfeld, Lisa, Marshall, Christian R., Mitchell, James E., Okazaki, Satoshi, Otsuka, Ikuo, Pinto, Dalila, Powers, Abigail, Ramoz, Nicolas, Ripke, Stephan, Roepke, Stefan, Rozanov, Vsevolod, Scherer, Stephen W., Schmahl, Christian, Sokolowski, Marcus, Starnawska, Anna, Strober, Michael, Su, Mei Hsin, Thornton, Laura M., Treasure, Janet, Ware, Erin B., Watson, Hunna J., Witt, Stephanie H., Blake Woodside, D., Yilmaz, Zeynep, Zillich, Lea, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Alfredsson, Lars, Appadurai, Vivek, Artigas, María Soler, Van Der Auwera, Sandra, Helena Azevedo, M., Bass, Nicholas, Bau, Claiton H.D., Baune, Bernhard T., Bellivier, Frank, Berger, Klaus, Biernacka, Joanna M., Bigdeli, Tim B., Binder, Elisabeth B., Boehnke, Michael, Boks, Marco P., Braff, David L., Bryant, Richard, Budde, Monika, Byrne, Enda M., Cahn, Wiepke, Castelao, Enrique, Cervilla, Jorge A., Chaumette, Boris, Corvin, Aiden, Craddock, Nicholas, Djurovic, Srdjan, Foo, Jerome C., Forstner, Andreas J., Frye, Mark, Gatt, Justine M., Giegling, Ina, Grabe, Hans J., Green, Melissa J., Grevet, Eugenio H., Grigoroiu-Serbanescu, Maria, Gutierrez, Blanca, Guzman-Parra, Jose, Hamshere, Marian L., Hartmann, Annette M., Hauser, Joanna, Heilmann-Heimbach, Stefanie, Hoffmann, Per, Ising, Marcus, Jones, Ian, Jones, Lisa A., Jonsson, Lina, Kahn, René S., Kelsoe, John R., Kendler, Kenneth S., Kloiber, Stefan, Koenen, Karestan C., Kogevinas, Manolis, Krebs, Marie Odile, Landén, Mikael, Leboyer, Marion, Lee, Phil H., Levinson, Douglas F., Liao, Calwing, Lissowska, Jolanta, Mayoral, Fermin, McElroy, Susan L., McGrath, Patrick, McGuffin, Peter, McQuillin, Andrew, Mehta, Divya, Melle, Ingrid, Mitchell, Philip B., Molina, Esther, Morken, Gunnar, Nievergelt, Caroline, Nöthen, Markus M., O'Donovan, Michael C., Ophoff, Roel A., Owen, Michael J., Pato, Carlos, Pato, Michele T., Penninx, Brenda W.J.H., Potash, James B., Power, Robert A., Preisig, Martin, Quested, Digby, Ramos-Quiroga, Josep Antoni, Reif, Andreas, Ribasés, Marta, Richarte, Vanesa, Rietschel, Marcella, Rivera, Margarita, Roberts, Andrea, Roberts, Gloria, Rouleau, Guy A., Rovaris, Diego L., Sanders, Alan R., Schofield, Peter R., Schulze, Thomas G., Scott, Laura J., Serretti, Alessandro, Shi, Jianxin, Sirignano, Lea, Sklar, Pamela, Smeland, Olav B., Smoller, Jordan W., Sonuga-Barke, Edmund J.S., Trzaskowski, MacIej, Tsuang, Ming T., Turecki, Gustavo, Vilar-Ribó, Laura, Vincent, John B., Völzke, Henry, Walters, James T.R., Weickert, Cynthia Shannon, Weickert, Thomas W., Weissman, Myrna M., Williams, Leanne M., Wray, Naomi R., Zai, Clement C., Agerbo, Esben, Børglum, Anders D., Breen, Gerome, Demontis, Ditte, Erlangsen, Annette, Gelernter, Joel, Glatt, Stephen J., Hougaard, David M., Hwu, Hai Gwo, Kuo, Po Hsiu, Lewis, Cathryn M., Li, Qingqin S., Liu, Chih Min, Martin, Nicholas G., McIntosh, Andrew M., Medland, Sarah E., Mors, Ole, Nordentoft, Merete, Olsen, Catherine M., Porteous, David, Smith, Daniel J., Stahl, Eli A., Stein, Murray B., Wasserman, Danuta, Werge, Thomas, Whiteman, David C., Willour, Virginia, Coon, Hilary, Beckham, Jean C., Kimbrel, Nathan A., Ruderfer, Douglas M., Docherty, Anna R., Mullins, Niamh, Ashley-Koch, Allison E., Qin, Xuejun, Coleman, Jonathan R.I., Shabalin, Andrey, Kang, Joo Eun, Murnyak, Balasz, Wendt, Frank, Adams, Mark, Campos, Adrian I., DiBlasi, Emily, Fullerton, Janice M., Kranzler, Henry R., Bakian, Amanda V., Monson, Eric T., Rentería, Miguel E., Walss-Bass, Consuelo, Andreassen, Ole A., Behera, Chittaranjan, Bulik, Cynthia M., Edenberg, Howard J., Kessler, Ronald C., John Mann, J., Nurnberger, John I., Pistis, Giorgio, Streit, Fabian, Ursano, Robert J., Polimanti, Renato, Dennis, Michelle, Garrett, Melanie, Hair, Lauren, Harvey, Philip, Hauser, Elizabeth R., Hauser, Michael A., Huffman, Jennifer, Jacobson, Daniel, Madduri, Ravi, McMahon, Benjamin, Oslin, David W., Trafton, Jodie, Awasthi, Swapnil, Berrettini, Wade H., Bohus, Martin, Chang, Xiao, Chen, Hsi Chung, Chen, Wei J., Christensen, Erik D.M.D., Crow, Scott, Duriez, Philibert, Edwards, Alexis C., Fernández-Aranda, Fernando, Galfalvy, Hanga, Gandal, Michael, Gorwood, Philip, Guo, Yiran, Hafferty, Jonathan D., Hakonarson, Hakon, Halmi, Katherine A., Hishimoto, Akitoyo, Jain, Sonia, Jamain, Stéphane, Jiménez-Murcia, Susana, Johnson, Craig, Kaplan, Allan S., Kaye, Walter H., Keel, Pamela K., Kennedy, James L., Kim, Minsoo, Klump, Kelly L., Levey, Daniel F., Li, Dong, Liao, Shih Cheng, Lieb, Klaus, Lilenfeld, Lisa, Marshall, Christian R., Mitchell, James E., Okazaki, Satoshi, Otsuka, Ikuo, Pinto, Dalila, Powers, Abigail, Ramoz, Nicolas, Ripke, Stephan, Roepke, Stefan, Rozanov, Vsevolod, Scherer, Stephen W., Schmahl, Christian, Sokolowski, Marcus, Starnawska, Anna, Strober, Michael, Su, Mei Hsin, Thornton, Laura M., Treasure, Janet, Ware, Erin B., Watson, Hunna J., Witt, Stephanie H., Blake Woodside, D., Yilmaz, Zeynep, Zillich, Lea, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Alfredsson, Lars, Appadurai, Vivek, Artigas, María Soler, Van Der Auwera, Sandra, Helena Azevedo, M., Bass, Nicholas, Bau, Claiton H.D., Baune, Bernhard T., Bellivier, Frank, Berger, Klaus, Biernacka, Joanna M., Bigdeli, Tim B., Binder, Elisabeth B., Boehnke, Michael, Boks, Marco P., Braff, David L., Bryant, Richard, Budde, Monika, Byrne, Enda M., Cahn, Wiepke, Castelao, Enrique, Cervilla, Jorge A., Chaumette, Boris, Corvin, Aiden, Craddock, Nicholas, Djurovic, Srdjan, Foo, Jerome C., Forstner, Andreas J., Frye, Mark, Gatt, Justine M., Giegling, Ina, Grabe, Hans J., Green, Melissa J., Grevet, Eugenio H., Grigoroiu-Serbanescu, Maria, Gutierrez, Blanca, Guzman-Parra, Jose, Hamshere, Marian L., Hartmann, Annette M., Hauser, Joanna, Heilmann-Heimbach, Stefanie, Hoffmann, Per, Ising, Marcus, Jones, Ian, Jones, Lisa A., Jonsson, Lina, Kahn, René S., Kelsoe, John R., Kendler, Kenneth S., Kloiber, Stefan, Koenen, Karestan C., Kogevinas, Manolis, Krebs, Marie Odile, Landén, Mikael, Leboyer, Marion, Lee, Phil H., Levinson, Douglas F., Liao, Calwing, Lissowska, Jolanta, Mayoral, Fermin, McElroy, Susan L., McGrath, Patrick, McGuffin, Peter, McQuillin, Andrew, Mehta, Divya, Melle, Ingrid, Mitchell, Philip B., Molina, Esther, Morken, Gunnar, Nievergelt, Caroline, Nöthen, Markus M., O'Donovan, Michael C., Ophoff, Roel A., Owen, Michael J., Pato, Carlos, Pato, Michele T., Penninx, Brenda W.J.H., Potash, James B., Power, Robert A., Preisig, Martin, Quested, Digby, Ramos-Quiroga, Josep Antoni, Reif, Andreas, Ribasés, Marta, Richarte, Vanesa, Rietschel, Marcella, Rivera, Margarita, Roberts, Andrea, Roberts, Gloria, Rouleau, Guy A., Rovaris, Diego L., Sanders, Alan R., Schofield, Peter R., Schulze, Thomas G., Scott, Laura J., Serretti, Alessandro, Shi, Jianxin, Sirignano, Lea, Sklar, Pamela, Smeland, Olav B., Smoller, Jordan W., Sonuga-Barke, Edmund J.S., Trzaskowski, MacIej, Tsuang, Ming T., Turecki, Gustavo, Vilar-Ribó, Laura, Vincent, John B., Völzke, Henry, Walters, James T.R., Weickert, Cynthia Shannon, Weickert, Thomas W., Weissman, Myrna M., Williams, Leanne M., Wray, Naomi R., Zai, Clement C., Agerbo, Esben, Børglum, Anders D., Breen, Gerome, Demontis, Ditte, Erlangsen, Annette, Gelernter, Joel, Glatt, Stephen J., Hougaard, David M., Hwu, Hai Gwo, Kuo, Po Hsiu, Lewis, Cathryn M., Li, Qingqin S., Liu, Chih Min, Martin, Nicholas G., McIntosh, Andrew M., Medland, Sarah E., Mors, Ole, Nordentoft, Merete, Olsen, Catherine M., Porteous, David, Smith, Daniel J., Stahl, Eli A., Stein, Murray B., Wasserman, Danuta, Werge, Thomas, Whiteman, David C., Willour, Virginia, Coon, Hilary, Beckham, Jean C., Kimbrel, Nathan A., and Ruderfer, Douglas M.

Abstract

Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide asso-ciation studies (GWASs) recently discovered and cross- validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic co-horts from both studies to conduct the largest GWAS meta- analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry ad-mixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and ge-netic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10–8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10–80). Significant brain tissue gene expression and drug set en-richment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major de-pressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical pheno-types. These findings provide insight into genetic fa, Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attemp

Published
2023

47. The impact of rare variation on gene expression across tissues

Author

Li, Xin, Kim, Yungil, Tsang, Emily K., Davis, Joe R., Damani, Farhan N., Chiang, Colby, Hess, Gaelen T., Zappala, Zachary, Strober, Benjamin J., Scott, Alexandra J., Li, Amy, Ganna, Andrea, Bassik, Michael C., Merker, Jason D., Aguet, Franois, Ardlie, Kristin G., Cummings, Beryl B., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Karczewski, Konrad J., Lek, Monkol, Li, Xiao, MacArthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segr, Ayellet V., Trowbridge, Casandra A., Tukiainen, Taru, Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Castel, Stephane E., Chen, Lin S., Conrad, Donald F., Cox, Nancy J., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frsard, Laure, Gamazon, Eric R., Garrido-Martn, Diego, Gewirtz, Ariel D.H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I., McDowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Sul, Jae Hoon, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Billy Li, Jin, Li, Qin, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Wu, Fan, Zhang, Rui, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., McLean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, and Zhu, Jingchun

Subjects
Disease susceptibility -- Genetic aspects, Genetic variation -- Observations, Gene expression -- Observations, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Xin Li [1]; Yungil Kim [2]; Emily K. Tsang [1, 3]; Joe R. Davis [1, 4]; Farhan N. Damani [2]; Colby Chiang [5]; Gaelen T. Hess [4]; Zachary Zappala [...]

Published
2017
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48. Dynamic landscape and regulation of RNA editing in mammals

Author

Tan, Meng How, Li, Qin, Shanmugam, Raghuvaran, Piskol, Robert, Kohler, Jennefer, Young, Amy N., Liu, Kaiwen Ivy, Zhang, Rui, Ramaswami, Gokul, Ariyoshi, Kentaro, Gupte, Ankita, Keegan, Liam P., George, Cyril X., Ramu, Avinash, Huang, Ni, Pollina, Elizabeth A., Leeman, Dena S., Rustighi, Alessandra, Goh, Y. P. Sharon, Aguet, Franois, Ardlie, Kristin G., Cummings, Beryl B., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Karczewski, Konrad J., Lek, Monkol, Li, Xiao, MacArthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segr, Ayellet V., Trowbridge, Casandra A., Tukiainen, Taru, Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Castel, Stephane E., Chen, Lin S., Chiang, Colby, Conrad, Donald F., Cox, Nancy J., Damani, Farhan N., Davis, Joe R., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frsard, Laure, Gamazon, Eric R., Garrido-Martn, Diego, Gewirtz, Ariel D. H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I., McDowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J., Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Strober, Benjamin J., Sul, Jae Hoon, Tsang, Emily K., Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zappala, Zachary, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Li, Jin Billy, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Wu, Fan, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., McLean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, Zhu, Jingchun, Chawla, Ajay, Del Sal, Giannino, Peltz, Gary, Brunet, Anne, Samuel, Charles E., OConnell, Mary A., Walkley, Carl R., and Nishikura, Kazuko

Subjects
Genetic research, Mammals -- Genetic aspects, RNA processing -- Research, Genetic regulation, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Meng How Tan (corresponding author) [1, 2, 3]; Qin Li [1]; Raghuvaran Shanmugam [2, 3]; Robert Piskol [1]; Jennefer Kohler [1]; Amy N. Young [1]; Kaiwen Ivy Liu [3]; [...]

Published
2017
Full Text
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49. Landscape of X chromosome inactivation across human tissues

Author

Tukiainen, Taru, Villani, Alexandra-Chlo, Yen, Angela, Rivas, Manuel A., Marshall, Jamie L., Satija, Rahul, Aguirre, Matt, Gauthier, Laura, Fleharty, Mark, Kirby, Andrew, Cummings, Beryl B., Castel, Stephane E., Karczewski, Konrad J., Aguet, Franois, Byrnes, Andrea, Ardlie, Kristin G., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Lek, Monkol, Li, Xiao, MacArthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segr, Ayellet V., Trowbridge, Casandra A., Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Chen, Lin S., Chiang, Colby, Conrad, Donald F., Cox, Nancy J., Damani, Farhan N., Davis, Joe R., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frsard, Laure, Gamazon, Eric R., Garrido-Martn, Diego, Gewirtz, Ariel D. H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I., McDowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J., Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Strober, Benjamin J., Sul, Jae Hoon, Tsang, Emily K., Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zappala, Zachary, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Li, Jin Billy, Li, Qin, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Wu, Fan, Zhang, Rui, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., McLean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, Zhu, Jingchun, Regev, Aviv, and Hacohen, Nir

Subjects
Chromosomes -- Physiological aspects, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Taru Tukiainen (corresponding author) [1, 2]; Alexandra-Chlo Villani [2, 3]; Angela Yen [2, 4]; Manuel A. Rivas [1, 2, 5]; Jamie L. Marshall [1, 2]; Rahul Satija [2, 6, [...]

Published
2017
Full Text
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50. Genome-wide association study meta-analysis of suicide death and suicidal behavior

Author

FinnGen, Int Suicide Genetics Consortium, Li, Qingqin S., Shabalin, Andrey A., DiBlasi, Emily, Palotie, Aarno, Coon, Hilary, University of Helsinki, Institute for Molecular Medicine Finland, Research Programs Unit, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, and Genomics of Neurological and Neuropsychiatric Disorders

Subjects
RISK, MUTATIONS, MIXED-MODEL ANALYSIS, PSYCHIATRIC-DISORDERS, 3112 Neurosciences, PSYCHOPATHIC TENDENCIES, DEPRESSION, CO-TWINS, GENE, 3124 Neurology and psychiatry, Cellular and Molecular Neuroscience, Psychiatry and Mental health, 1182 Biochemistry, cell and molecular biology, NEUROLIGINS, 3111 Biomedicine, AUTISM, Molecular Biology
Abstract

Suicide is a worldwide health crisis. We aimed to identify genetic risk variants associated with suicide death and suicidal behavior. Meta-analysis for suicide death was performed using 3765 cases from Utah and matching 6572 controls of European ancestry. Meta-analysis for suicidal behavior using data across five cohorts (n = 8315 cases and 256,478 psychiatric or populational controls of European ancestry) was also performed. One locus in neuroligin 1 (NLGN1) passing the genome-wide significance threshold for suicide death was identified (top SNP rs73182688, with p = 5.48 × 10−8 before and p = 4.55 × 10−8 after mtCOJO analysis conditioning on MDD to remove genetic effects on suicide mediated by MDD). Conditioning on suicidal attempts did not significantly change the association strength (p = 6.02 × 10−8), suggesting suicide death specificity. NLGN1 encodes a member of a family of neuronal cell surface proteins. Members of this family act as splice site-specific ligands for beta-neurexins and may be involved in synaptogenesis. The NRXN-NLGN pathway was previously implicated in suicide, autism, and schizophrenia. We additionally identified ROBO2 and ZNF28 associations with suicidal behavior in the meta-analysis across five cohorts in gene-based association analysis using MAGMA. Lastly, we replicated two loci including variants near SOX5 and LOC101928519 associated with suicidal attempts identified in the ISGC and MVP meta-analysis using the independent FinnGen samples. Suicide death and suicidal behavior showed positive genetic correlations with depression, schizophrenia, pain, and suicidal attempt, and negative genetic correlation with educational attainment. These correlations remained significant after conditioning on depression, suggesting pleiotropic effects among these traits. Bidirectional generalized summary-data-based Mendelian randomization analysis suggests that genetic risk for the suicidal attempt and suicide death are both bi-directionally causal for MDD.

Published
2023

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