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5,102 results on '"Faraone, Stephen"'

1. A New Perspective on ADHD Research: Knowledge Graph Construction with LLMs and Network Based Insights

Author

Otal, Hakan T., Faraone, Stephen V., and Canbaz, M. Abdullah

Subjects
Computer Science - Social and Information Networks, Computer Science - Computation and Language, 68T30, 68T50, 92C30, I.2.4, I.2.7, J.3
Abstract

Attention-Deficit/Hyperactivity Disorder (ADHD) is a challenging disorder to study due to its complex symptomatology and diverse contributing factors. To explore how we can gain deeper insights on this topic, we performed a network analysis on a comprehensive knowledge graph (KG) of ADHD, constructed by integrating scientific literature and clinical data with the help of cutting-edge large language models. The analysis, including k-core techniques, identified critical nodes and relationships that are central to understanding the disorder. Building on these findings, we developed a context-aware chatbot using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), enabling accurate and informed interactions. Our knowledge graph not only advances the understanding of ADHD but also provides a powerful tool for research and clinical applications., Comment: 14 pages, 2 figures

Published
2024

5. Attention-deficit/hyperactivity disorder

Author

Faraone, Stephen V., Bellgrove, Mark A., Brikell, Isabell, Cortese, Samuele, Hartman, Catharina A., Hollis, Chris, Newcorn, Jeffrey H., Philipsen, Alexandra, Polanczyk, Guilherme V., Rubia, Katya, Sibley, Margaret H., and Buitelaar, Jan K.

Published
2024
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8. A primer on the use of machine learning to distil knowledge from data in biological psychiatry

Author

Quinn, Thomas P., Hess, Jonathan L., Marshe, Victoria S., Barnett, Michelle M., Hauschild, Anne-Christin, Maciukiewicz, Malgorzata, Elsheikh, Samar S. M., Men, Xiaoyu, Schwarz, Emanuel, Trakadis, Yannis J., Breen, Michael S., Barnett, Eric J., Zhang-James, Yanli, Ahsen, Mehmet Eren, Cao, Han, Chen, Junfang, Hou, Jiahui, Salekin, Asif, Lin, Ping-I, Nicodemus, Kristin K., Meyer-Lindenberg, Andreas, Bichindaritz, Isabelle, Faraone, Stephen V., Cairns, Murray J., Pandey, Gaurav, Müller, Daniel J., and Glatt, Stephen J.

Published
2024
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9. Neurobiology of Attention Deficit Hyperactivity Disorder

Author

Faraone, Stephen V., Radonjić, Nevena V., Schulze, Thomas G., Section editor, Laje, Gonzalo, Section editor, Tasman, Allan, editor, Riba, Michelle B., editor, Alarcón, Renato D., editor, Alfonso, César A., editor, Kanba, Shigenobu, editor, Lecic-Tosevski, Dusica, editor, Ndetei, David M., editor, Ng, Chee H., editor, and Schulze, Thomas G., editor

Published
2024
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10. Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains.

Author

Demontis, Ditte, Walters, G, Athanasiadis, Georgios, Walters, Raymond, Therrien, Karen, Nielsen, Trine, Farajzadeh, Leila, Voloudakis, Georgios, Bendl, Jaroslav, Zeng, Biau, Zhang, Wen, Grove, Jakob, Als, Thomas, Duan, Jinjie, Satterstrom, F, Bybjerg-Grauholm, Jonas, Bækved-Hansen, Marie, Gudmundsson, Olafur, Magnusson, Sigurdur, Baldursson, Gisli, Davidsdottir, Katrin, Haraldsdottir, Gyda, Agerbo, Esben, Hoffman, Gabriel, Dalsgaard, Søren, Martin, Joanna, Ribasés, Marta, Boomsma, Dorret, Soler Artigas, Maria, Roth Mota, Nina, Howrigan, Daniel, Medland, Sarah, Zayats, Tetyana, Rajagopal, Veera, Nordentoft, Merete, Mors, Ole, Hougaard, David, Mortensen, Preben, Daly, Mark, Faraone, Stephen, Stefansson, Hreinn, Roussos, Panos, Franke, Barbara, Werge, Thomas, Neale, Benjamin, Stefansson, Kari, and Børglum, Anders

Subjects
Humans, Genome-Wide Association Study, Attention Deficit Disorder with Hyperactivity, Brain, Cognition, Genetic Predisposition to Disease
Abstract

Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder with a major genetic component. Here, we present a genome-wide association study meta-analysis of ADHD comprising 38,691 individuals with ADHD and 186,843 controls. We identified 27 genome-wide significant loci, highlighting 76 potential risk genes enriched among genes expressed particularly in early brain development. Overall, ADHD genetic risk was associated with several brain-specific neuronal subtypes and midbrain dopaminergic neurons. In exome-sequencing data from 17,896 individuals, we identified an increased load of rare protein-truncating variants in ADHD for a set of risk genes enriched with probable causal common variants, potentially implicating SORCS3 in ADHD by both common and rare variants. Bivariate Gaussian mixture modeling estimated that 84-98% of ADHD-influencing variants are shared with other psychiatric disorders. In addition, common-variant ADHD risk was associated with impaired complex cognition such as verbal reasoning and a range of executive functions, including attention.

Published
2023

12. Incidence, prevalence, and global burden of ADHD from 1990 to 2019 across 204 countries: data, with critical re-analysis, from the Global Burden of Disease study

Author

Cortese, Samuele, Song, Minjin, Farhat, Luis C., Yon, Dong Keon, Lee, Seung Won, Kim, Min Seo, Park, Seoyeon, Oh, Jae Won, Lee, San, Cheon, Keun-Ah, Smith, Lee, Gosling, Corentin J., Polanczyk, Guilherme V., Larsson, Henrik, Rohde, Luis A., Faraone, Stephen V., Koyanagi, Ai, Dragioti, Elena, Radua, Joaquim, Carvalho, Andre F., Il Shin, Jae, and Solmi, Marco

Published
2023
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13. BrainGENIE: The Brain Gene Expression and Network Imputation Engine

Author

Hess, Jonathan L, Quinn, Thomas P, Zhang, Chunling, Hearn, Gentry C, Chen, Samuel, Kong, Sek Won, Cairns, Murray, Tsuang, Ming T, Faraone, Stephen V, and Glatt, Stephen J

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Brain Disorders, Human Genome, Schizophrenia, Genetics, Mental Health, Biotechnology, Bioengineering, Mental health, Humans, Genome-Wide Association Study, Genotype, Gene Expression Profiling, Transcriptome, Brain, Neuropsychiatric Consortium for Analysis and Sharing of Transcriptomes, Public Health and Health Services, Clinical sciences, Biological psychology
Abstract

In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood-brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947-11,816 genes (false-discovery rate-adjusted p

Published
2023

15. Polygenic association between attention-deficit/hyperactivity disorder liability and cognitive impairments

Author

Vainieri, Isabella, Martin, Joanna, Rommel, Anna-Sophie, Asherson, Philip, Banaschewski, Tobias, Buitelaar, Jan, Cormand, Bru, Crosbie, Jennifer, Faraone, Stephen V, Franke, Barbara, Loo, Sandra K, Miranda, Ana, Manor, Iris, Oades, Robert D, Purves, Kirstin L, Ramos-Quiroga, J Antoni, Ribasés, Marta, Roeyers, Herbert, Rothenberger, Aribert, Schachar, Russell, Sergeant, Joseph, Steinhausen, Hans-Christoph, Vuijk, Pieter J, Doyle, Alysa E, and Kuntsi, Jonna

Subjects
Attention Deficit Hyperactivity Disorder (ADHD), Genetics, Prevention, Human Genome, Mental Health, 2.1 Biological and endogenous factors, Aetiology, Adolescent, Adult, Child, Humans, Young Adult, Attention Deficit Disorder with Hyperactivity, Cognitive Dysfunction, Genome-Wide Association Study, Phenotype, Reaction Time, Case-Control Studies, ADHD, attention, cognition, inhibition, polygenic risk scores, reaction time variability, Neurosciences, Public Health and Health Services, Psychology, Psychiatry
Abstract

BackgroundA recent genome-wide association study (GWAS) identified 12 independent loci significantly associated with attention-deficit/hyperactivity disorder (ADHD). Polygenic risk scores (PRS), derived from the GWAS, can be used to assess genetic overlap between ADHD and other traits. Using ADHD samples from several international sites, we derived PRS for ADHD from the recent GWAS to test whether genetic variants that contribute to ADHD also influence two cognitive functions that show strong association with ADHD: attention regulation and response inhibition, captured by reaction time variability (RTV) and commission errors (CE).MethodsThe discovery GWAS included 19 099 ADHD cases and 34 194 control participants. The combined target sample included 845 people with ADHD (age: 8-40 years). RTV and CE were available from reaction time and response inhibition tasks. ADHD PRS were calculated from the GWAS using a leave-one-study-out approach. Regression analyses were run to investigate whether ADHD PRS were associated with CE and RTV. Results across sites were combined via random effect meta-analyses.ResultsWhen combining the studies in meta-analyses, results were significant for RTV (R2 = 0.011, β = 0.088, p = 0.02) but not for CE (R2 = 0.011, β = 0.013, p = 0.732). No significant association was found between ADHD PRS and RTV or CE in any sample individually (p > 0.10).ConclusionsWe detected a significant association between PRS for ADHD and RTV (but not CE) in individuals with ADHD, suggesting that common genetic risk variants for ADHD influence attention regulation.

Published
2022

17. Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Author

Trubetskoy, Vassily, Pardiñas, Antonio F, Qi, Ting, Panagiotaropoulou, Georgia, Awasthi, Swapnil, Bigdeli, Tim B, Bryois, Julien, Chen, Chia-Yen, Dennison, Charlotte A, Hall, Lynsey S, Lam, Max, Watanabe, Kyoko, Frei, Oleksandr, Ge, Tian, Harwood, Janet C, Koopmans, Frank, Magnusson, Sigurdur, Richards, Alexander L, Sidorenko, Julia, Wu, Yang, Zeng, Jian, Grove, Jakob, Kim, Minsoo, Li, Zhiqiang, Voloudakis, Georgios, Zhang, Wen, Adams, Mark, Agartz, Ingrid, Atkinson, Elizabeth G, Agerbo, Esben, Al Eissa, Mariam, Albus, Margot, Alexander, Madeline, Alizadeh, Behrooz Z, Alptekin, Köksal, Als, Thomas D, Amin, Farooq, Arolt, Volker, Arrojo, Manuel, Athanasiu, Lavinia, Azevedo, Maria Helena, Bacanu, Silviu A, Bass, Nicholas J, Begemann, Martin, Belliveau, Richard A, Bene, Judit, Benyamin, Beben, Bergen, Sarah E, Blasi, Giuseppe, Bobes, Julio, Bonassi, Stefano, Braun, Alice, Bressan, Rodrigo Affonseca, Bromet, Evelyn J, Bruggeman, Richard, Buckley, Peter F, Buckner, Randy L, Bybjerg-Grauholm, Jonas, Cahn, Wiepke, Cairns, Murray J, Calkins, Monica E, Carr, Vaughan J, Castle, David, Catts, Stanley V, Chambert, Kimberley D, Chan, Raymond CK, Chaumette, Boris, Cheng, Wei, Cheung, Eric FC, Chong, Siow Ann, Cohen, David, Consoli, Angèle, Cordeiro, Quirino, Costas, Javier, Curtis, Charles, Davidson, Michael, Davis, Kenneth L, de Haan, Lieuwe, Degenhardt, Franziska, DeLisi, Lynn E, Demontis, Ditte, Dickerson, Faith, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Duan, Jubao, Ducci, Giuseppe, Dudbridge, Frank, Eriksson, Johan G, Fañanás, Lourdes, Faraone, Stephen V, Fiorentino, Alessia, Forstner, Andreas, Frank, Josef, Freimer, Nelson B, Fromer, Menachem, Frustaci, Alessandra, Gadelha, Ary, Genovese, Giulio, and Gershon, Elliot S

Subjects
Brain Disorders, Human Genome, Mental Health, Schizophrenia, Serious Mental Illness, Biotechnology, Neurosciences, Genetics, Aetiology, 2.1 Biological and endogenous factors, Alleles, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Indonesia Schizophrenia Consortium, PsychENCODE, Psychosis Endophenotypes International Consortium, SynGO Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, General Science & Technology
Abstract

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Published
2022

18. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Author

Cramer, Estee Y, Ray, Evan L, Lopez, Velma K, Bracher, Johannes, Brennen, Andrea, Rivadeneira, Alvaro J Castro, Gerding, Aaron, Gneiting, Tilmann, House, Katie H, Huang, Yuxin, Jayawardena, Dasuni, Kanji, Abdul H, Khandelwal, Ayush, Le, Khoa, Mühlemann, Anja, Niemi, Jarad, Shah, Apurv, Stark, Ariane, Wang, Yijin, Wattanachit, Nutcha, Zorn, Martha W, Gu, Youyang, Jain, Sansiddh, Bannur, Nayana, Deva, Ayush, Kulkarni, Mihir, Merugu, Srujana, Raval, Alpan, Shingi, Siddhant, Tiwari, Avtansh, White, Jerome, Abernethy, Neil F, Woody, Spencer, Dahan, Maytal, Fox, Spencer, Gaither, Kelly, Lachmann, Michael, Meyers, Lauren Ancel, Scott, James G, Tec, Mauricio, Srivastava, Ajitesh, George, Glover E, Cegan, Jeffrey C, Dettwiller, Ian D, England, William P, Farthing, Matthew W, Hunter, Robert H, Lafferty, Brandon, Linkov, Igor, Mayo, Michael L, Parno, Matthew D, Rowland, Michael A, Trump, Benjamin D, Zhang-James, Yanli, Chen, Samuel, Faraone, Stephen V, Hess, Jonathan, Morley, Christopher P, Salekin, Asif, Wang, Dongliang, Corsetti, Sabrina M, Baer, Thomas M, Eisenberg, Marisa C, Falb, Karl, Huang, Yitao, Martin, Emily T, McCauley, Ella, Myers, Robert L, Schwarz, Tom, Sheldon, Daniel, Gibson, Graham Casey, Yu, Rose, Gao, Liyao, Ma, Yian, Wu, Dongxia, Yan, Xifeng, Jin, Xiaoyong, Wang, Yu-Xiang, Chen, YangQuan, Guo, Lihong, Zhao, Yanting, Gu, Quanquan, Chen, Jinghui, Wang, Lingxiao, Xu, Pan, Zhang, Weitong, Zou, Difan, Biegel, Hannah, Lega, Joceline, McConnell, Steve, Nagraj, VP, Guertin, Stephanie L, Hulme-Lowe, Christopher, Turner, Stephen D, Shi, Yunfeng, Ban, Xuegang, Walraven, Robert, Hong, Qi-Jun, Kong, Stanley, and van de Walle, Axel

Subjects
Bioengineering, Good Health and Well Being, COVID-19, Data Accuracy, Forecasting, Humans, Pandemics, Probability, Public Health, United States, forecasting, ensemble forecast, model evaluation
Abstract

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

Published
2022

19. Rare coding variants in ten genes confer substantial risk for schizophrenia.

Author

Singh, Tarjinder, Poterba, Timothy, Curtis, David, Akil, Huda, Al Eissa, Mariam, Barchas, Jack D, Bass, Nicholas, Bigdeli, Tim B, Breen, Gerome, Bromet, Evelyn J, Buckley, Peter F, Bunney, William E, Bybjerg-Grauholm, Jonas, Byerley, William F, Chapman, Sinéad B, Chen, Wei J, Churchhouse, Claire, Craddock, Nicholas, Cusick, Caroline M, DeLisi, Lynn, Dodge, Sheila, Escamilla, Michael A, Eskelinen, Saana, Fanous, Ayman H, Faraone, Stephen V, Fiorentino, Alessia, Francioli, Laurent, Gabriel, Stacey B, Gage, Diane, Gagliano Taliun, Sarah A, Ganna, Andrea, Genovese, Giulio, Glahn, David C, Grove, Jakob, Hall, Mei-Hua, Hämäläinen, Eija, Heyne, Henrike O, Holi, Matti, Hougaard, David M, Howrigan, Daniel P, Huang, Hailiang, Hwu, Hai-Gwo, Kahn, René S, Kang, Hyun Min, Karczewski, Konrad J, Kirov, George, Knowles, James A, Lee, Francis S, Lehrer, Douglas S, Lescai, Francesco, Malaspina, Dolores, Marder, Stephen R, McCarroll, Steven A, McIntosh, Andrew M, Medeiros, Helena, Milani, Lili, Morley, Christopher P, Morris, Derek W, Mortensen, Preben Bo, Myers, Richard M, Nordentoft, Merete, O'Brien, Niamh L, Olivares, Ana Maria, Ongur, Dost, Ouwehand, Willem H, Palmer, Duncan S, Paunio, Tiina, Quested, Digby, Rapaport, Mark H, Rees, Elliott, Rollins, Brandi, Satterstrom, F Kyle, Schatzberg, Alan, Scolnick, Edward, Scott, Laura J, Sharp, Sally I, Sklar, Pamela, Smoller, Jordan W, Sobell, Janet L, Solomonson, Matthew, Stahl, Eli A, Stevens, Christine R, Suvisaari, Jaana, Tiao, Grace, Watson, Stanley J, Watts, Nicholas A, Blackwood, Douglas H, Børglum, Anders D, Cohen, Bruce M, Corvin, Aiden P, Esko, Tõnu, Freimer, Nelson B, Glatt, Stephen J, Hultman, Christina M, McQuillin, Andrew, Palotie, Aarno, Pato, Carlos N, Pato, Michele T, Pulver, Ann E, and St Clair, David

Subjects
Humans, Genetic Predisposition to Disease, Receptors, N-Methyl-D-Aspartate, Case-Control Studies, Schizophrenia, Mutation, Exome, Neurodevelopmental Disorders, Human Genome, Biotechnology, Mental Health, Neurosciences, Brain Disorders, Genetics, Serious Mental Illness, Aetiology, 2.1 Biological and endogenous factors, Mental health, Neurological, General Science & Technology
Abstract

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P

Published
2022

22. Reproducibility in the absence of selective reporting: An illustration from large‐scale brain asymmetry research

Author

Kong, Xiang‐Zhen, Mathias, Samuel R, Guadalupe, Tulio, Abé, Christoph, Agartz, Ingrid, Akudjedu, Theophilus N, Aleman, Andre, Alhusaini, Saud, Allen, Nicholas B, Ames, David, Andreassen, Ole A, Vasquez, Alejandro Arias, Armstrong, Nicola J, Asherson, Phil, Bergo, Felipe, Bastin, Mark E, Batalla, Albert, Bauer, Jochen, Baune, Bernhard T, Baur‐Streubel, Ramona, Biederman, Joseph, Blaine, Sara K, Boedhoe, Premika, Bøen, Erlend, Bose, Anushree, Bralten, Janita, Brandeis, Daniel, Brem, Silvia, Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J, Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales‐Rodríguez, Erick Jorge, Cannon, Dara M, Caparelli, Elisabeth C, Castellanos, Francisco X, Cendes, Fernando, Chaim‐Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun‐lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Clark, Vincent P, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Córdova‐Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dannlowski, Udo, de Bruttopilo, Sara Ambrosino, de Zeeuw, Patrick, Deary, Ian J, Demeter, Damion V, Di Martino, Adriana, Dickie, Erin W, Dietsche, Bruno, Doan, Nhat Trung, Doherty, Colin P, Doyle, Alysa, Durston, Sarah, Earl, Eric, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N, Fair, Damien A, Faraone, Stephen V, Fernández, Guillén, Flint, Claas, Filho, Geraldo Busatto, Förster, Katharina, Fouche, Jean‐Paul, Foxe, John J, Frodl, Thomas, Fuentes‐Claramonte, Paola, Fullerton, Janice M, Garavan, Hugh, do Santos Garcia, Danielle, Gotlib, Ian H, Goudriaan, Anna E, Grabe, Hans Jörgen, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K, Harris, Mathew A, Hartman, Catharina A, del Carmen Valdés Hernández, Maria, and Heslenfeld, Dirk

Subjects
Biological Psychology, Psychology, Neurosciences, Neurological, Adolescent, Adult, Aged, Brain Cortical Thickness, Cerebral Cortex, Datasets as Topic, Humans, Magnetic Resonance Imaging, Middle Aged, Multicenter Studies as Topic, Neuroimaging, Publication Bias, Reproducibility of Results, Young Adult, ENIGMA Laterality Working Group, P-hacking, multisite collaboration, publication bias, reproducibility, team science, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes.

Published
2022

23. Polygenic resilience scores capture protective genetic effects for Alzheimer’s disease

Author

Hou, Jiahui, Hess, Jonathan L, Armstrong, Nicola, Bis, Joshua C, Grenier-Boley, Benjamin, Karlsson, Ida K, Leonenko, Ganna, Numbers, Katya, O’Brien, Eleanor K, Shadrin, Alexey, Thalamuthu, Anbupalam, Yang, Qiong, Andreassen, Ole A, Brodaty, Henry, Gatz, Margaret, Kochan, Nicole A, Lambert, Jean-Charles, Laws, Simon M, Masters, Colin L, Mather, Karen A, Pedersen, Nancy L, Posthuma, Danielle, Sachdev, Perminder S, Williams, Julie, Fan, Chun Chieh, Faraone, Stephen V, Fennema-Notestine, Christine, Lin, Shu-Ju, Escott-Price, Valentina, Holmans, Peter, Seshadri, Sudha, Tsuang, Ming T, Kremen, William S, and Glatt, Stephen J

Subjects
Genetics, Alzheimer's Disease, Brain Disorders, Human Genome, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Genetic Testing, Neurodegenerative, Prevention, Dementia, Aging, Acquired Cognitive Impairment, Aetiology, 2.1 Biological and endogenous factors, Alzheimer Disease, Apolipoprotein E4, Apolipoproteins E, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Risk Factors, Alzheimer’s Disease Neuroimaging Initiative, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Published
2022

24. Preclinical Stage Alzheimer's Disease Detection Using Magnetic Resonance Image Scans

Author

Altay, Fatih, Sanchez, Guillermo Ramon, James, Yanli, Faraone, Stephen V., Velipasalar, Senem, and Salekin, Asif

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning
Abstract

Alzheimer's disease is one of the diseases that mostly affects older people without being a part of aging. The most common symptoms include problems with communicating and abstract thinking, as well as disorientation. It is important to detect Alzheimer's disease in early stages so that cognitive functioning would be improved by medication and training. In this paper, we propose two attention model networks for detecting Alzheimer's disease from MRI images to help early detection efforts at the preclinical stage. We also compare the performance of these two attention network models with a baseline model. Recently available OASIS-3 Longitudinal Neuroimaging, Clinical, and Cognitive Dataset is used to train, evaluate and compare our models. The novelty of this research resides in the fact that we aim to detect Alzheimer's disease when all the parameters, physical assessments, and clinical data state that the patient is healthy and showing no symptoms, Comment: 10 pages, 5 figures

Published
2020

25. Analysis of structural brain asymmetries in attention‐deficit/hyperactivity disorder in 39 datasets

Author

Postema, Merel C, Hoogman, Martine, Ambrosino, Sara, Asherson, Philip, Banaschewski, Tobias, Bandeira, Cibele E, Baranov, Alexandr, Bau, Claiton HD, Baumeister, Sarah, Baur‐Streubel, Ramona, Bellgrove, Mark A, Biederman, Joseph, Bralten, Janita, Brandeis, Daniel, Brem, Silvia, Buitelaar, Jan K, Busatto, Geraldo F, Castellanos, Francisco X, Cercignani, Mara, Chaim‐Avancini, Tiffany M, Chantiluke, Kaylita C, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Cubillo, Ana I, Cupertino, Renata B, de Zeeuw, Patrick, Doyle, Alysa E, Durston, Sarah, Earl, Eric A, Epstein, Jeffery N, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas J, Faraone, Stephen V, Frodl, Thomas, Gabel, Matt C, Gogberashvili, Tinatin, Grevet, Eugenio H, Haavik, Jan, Harrison, Neil A, Hartman, Catharina A, Heslenfeld, Dirk J, Hoekstra, Pieter J, Hohmann, Sarah, Høvik, Marie F, Jernigan, Terry L, Kardatzki, Bernd, Karkashadze, Georgii, Kelly, Clare, Kohls, Gregor, Konrad, Kerstin, Kuntsi, Jonna, Lazaro, Luisa, Lera‐Miguel, Sara, Lesch, Klaus‐Peter, Louza, Mario R, Lundervold, Astri J, Malpas, Charles B, Mattos, Paulo, McCarthy, Hazel, Namazova‐Baranova, Leyla, Nicolau, Rosa, Nigg, Joel T, Novotny, Stephanie E, Weiss, Eileen Oberwelland, Tuura, Ruth L O'Gorman, Oosterlaan, Jaap, Oranje, Bob, Paloyelis, Yannis, Pauli, Paul, Picon, Felipe A, Plessen, Kerstin J, Ramos‐Quiroga, J Antoni, Reif, Andreas, Reneman, Liesbeth, Rosa, Pedro GP, Rubia, Katya, Schrantee, Anouk, Schweren, Lizanne JS, Seitz, Jochen, Shaw, Philip, Silk, Tim J, Skokauskas, Norbert, Vila, Juan C Soliva, Stevens, Michael C, Sudre, Gustavo, Tamm, Leanne, Tovar‐Moll, Fernanda, van Erp, Theo GM, Vance, Alasdair, Vilarroya, Oscar, Vives‐Gilabert, Yolanda, von Polier, Georg G, Walitza, Susanne, Yoncheva, Yuliya N, Zanetti, Marcus V, Ziegler, Georg C, Glahn, David C, and Jahanshad, Neda

Subjects
Biological Psychology, Psychology, Pediatric, Brain Disorders, Mental Health, Neurosciences, Attention Deficit Hyperactivity Disorder (ADHD), Pediatric Research Initiative, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Brain, Caudate Nucleus, Child, Humans, Magnetic Resonance Imaging, Attention&#8208, deficit, hyperactivity disorder, brain asymmetry, brain laterality, structural MRI, large&#8208, scale data, ENIGMA ADHD Working Group, Attention-deficit, large-scale data, Clinical Sciences, Cognitive Sciences, Developmental & Child Psychology, Clinical sciences, Applied and developmental psychology, Clinical and health psychology
Abstract

ObjectiveSome studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.MethodsWe analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.ResultsThere was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.ConclusionPrior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

Published
2021

26. The World Federation of ADHD International Consensus Statement: 208 Evidence-based conclusions about the disorder

Author

Faraone, Stephen V, Banaschewski, Tobias, Coghill, David, Zheng, Yi, Biederman, Joseph, Bellgrove, Mark A, Newcorn, Jeffrey H, Gignac, Martin, Al Saud, Nouf M, Manor, Iris, Rohde, Luis Augusto, Yang, Li, Cortese, Samuele, Almagor, Doron, Stein, Mark A, Albatti, Turki H, Aljoudi, Haya F, Alqahtani, Mohammed MJ, Asherson, Philip, Atwoli, Lukoye, Bölte, Sven, Buitelaar, Jan K, Crunelle, Cleo L, Daley, David, Dalsgaard, Søren, Döpfner, Manfred, Espinet, Stacey, Fitzgerald, Michael, Franke, Barbara, Gerlach, Manfred, Haavik, Jan, Hartman, Catharina A, Hartung, Cynthia M, Hinshaw, Stephen P, Hoekstra, Pieter J, Hollis, Chris, Kollins, Scott H, Kooij, JJ Sandra, Kuntsi, Jonna, Larsson, Henrik, Li, Tingyu, Liu, Jing, Merzon, Eugene, Mattingly, Gregory, Mattos, Paulo, McCarthy, Suzanne, Mikami, Amori Yee, Molina, Brooke SG, Nigg, Joel T, Purper-Ouakil, Diane, Omigbodun, Olayinka O, Polanczyk, Guilherme V, Pollak, Yehuda, Poulton, Alison S, Rajkumar, Ravi Philip, Reding, Andrew, Reif, Andreas, Rubia, Katya, Rucklidge, Julia, Romanos, Marcel, Ramos-Quiroga, J Antoni, Schellekens, Arnt, Scheres, Anouk, Schoeman, Renata, Schweitzer, Julie B, Shah, Henal, Solanto, Mary V, Sonuga-Barke, Edmund, Soutullo, César, Steinhausen, Hans-Christoph, Swanson, James M, Thapar, Anita, Tripp, Gail, van de Glind, Geurt, van den Brink, Wim, Van der Oord, Saskia, Venter, Andre, Vitiello, Benedetto, Walitza, Susanne, and Wang, Yufeng

Subjects
Epidemiology, Health Sciences, Behavioral and Social Science, Clinical Research, Mental Illness, Brain Disorders, Comparative Effectiveness Research, Mental Health, Pediatric, Attention Deficit Hyperactivity Disorder (ADHD), Mental health, Attention Deficit Disorder with Hyperactivity, Humans, Network Meta-Analysis, Publication Bias, ADHD, Diagnosis, Treatment, Course, Outcome, Genetics, Brain, Medical and Health Sciences, Psychology and Cognitive Sciences, Behavioral Science & Comparative Psychology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundMisconceptions about ADHD stigmatize affected people, reduce credibility of providers, and prevent/delay treatment. To challenge misconceptions, we curated findings with strong evidence base.MethodsWe reviewed studies with more than 2000 participants or meta-analyses from five or more studies or 2000 or more participants. We excluded meta-analyses that did not assess publication bias, except for meta-analyses of prevalence. For network meta-analyses we required comparison adjusted funnel plots. We excluded treatment studies with waiting-list or treatment as usual controls. From this literature, we extracted evidence-based assertions about the disorder.ResultsWe generated 208 empirically supported statements about ADHD. The status of the included statements as empirically supported is approved by 80 authors from 27 countries and 6 continents. The contents of the manuscript are endorsed by 366 people who have read this document and agree with its contents.ConclusionsMany findings in ADHD are supported by meta-analysis. These allow for firm statements about the nature, course, outcome causes, and treatments for disorders that are useful for reducing misconceptions and stigma.

Published
2021

27. Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes

Author

Li, Ting, van Rooij, Daan, Mota, Nina Roth, Buitelaar, Jan K, Ambrosino, Sara, Banaschewski, Tobias, Bandeira, Cibele E, Bau, Claiton HD, Baumeister, Sarah, Baur‐Streubel, Ramona, Bellgrove, Mark A, Biederman, Joseph, Bralten, Janita, Bramati, Ivanei E, Brandeis, Daniel, Berm, Silvia, Busatto, Geraldo F, Calvo, Anna, Castellanos, Francisco X, Cercignani, Mara, Chantiluke, Kaylita C, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Cubillo, Ana I, Cupertino, Renata B, de Zeeuw, Parick, Durston, Sarah, Earl, Eric A, Epstein, Jeffery N, Ethofer, Thomas, Fallgatter, Andreas J, Fair, Damien A, Faraone, Stephen V, Frodl, Thomas, Gabel, Matt C, Gogberashvili, Tinatin, Grevet, Eugenio H, Haavik, Jan, Harrison, Neil A, Hartman, Catharina A, Heslenfeld, Dirk J, Hoekstra, Pieter J, Høvik, Marie F, Jahanshad, Neda, Kardatzki, Bernd, Karkashadze, Georgii, Kelly, Clare, Kohls, Gregor, Konrad, Kerstin, Kuntsi, Jonna, Lazaro, Luisa, Lera‐Miguel, Sara, Lesch, Klaus‐Peter, Louza, Mario R, Lundervold, Astri J, Malpas, Charles B, Mattos, Paulo, McCarthy, Hazel, Nicolau, Rosa, Nigg, Joel T, Tuura, Ruth L O'Gorman, Oosterlaan, Jaap, Oranje, Bob, Paloyelis, Yannis, Pauli, Paul, Picon, Felipe A, Plessen, Kerstin J, Ramos‐Quiroga, J Antoni, Reif, Andreas, Reneman, Liesbeth, Rosa, Pedro GP, Rubia, Katya, Schrantee, Anouk, Schweren, Lizanne JS, Seitz, Jochen, Shaw, Philip, Silk, Tim J, Skokauskas, Norbert, Vila, Juan Carlos Soliva, Soloveva, Anastasiia, Stevens, Michael C, Sudre, Gustavo, Tamm, Leanne, Thompson, Paul M, Tovar‐Moll, Fernanda, van Erp, Theo GM, Vance, Alasdair, Vilarroya, Oscar, Vives‐Gilabert, Yolanda, von Polier, Georg G, Walitza, Susanne, Yoncheva, Yuliya N, Zanetti, Marcus V, Ziegler, Georg C, Anikin, Anatoly, Asherson, Philip, Baranov, Alexandr, Chaim‐Avanicini, Tiffany, and Dale, Anders M

Subjects
Biological Psychology, Psychology, Mental Health, Pediatric, Brain Disorders, Attention Deficit Hyperactivity Disorder (ADHD), Clinical Research, Neurosciences, Adult, Attention Deficit Disorder with Hyperactivity, Brain, Case-Control Studies, Female, Humans, Magnetic Resonance Imaging, Male, Thalamus, ADHD, subcortical volume, neuroanatomic heterogeneity, community detection, effect sizes, ENIGMA ADHD Working Group, Clinical Sciences, Cognitive Sciences, Developmental & Child Psychology, Clinical sciences, Applied and developmental psychology, Clinical and health psychology
Abstract

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Neuroanatomic heterogeneity limits our understanding of ADHD's etiology. This study aimed to parse heterogeneity of ADHD and to determine whether patient subgroups could be discerned based on subcortical brain volumes.MethodsUsing the large ENIGMA-ADHD Working Group dataset, four subsamples of 993 boys with and without ADHD and to subsamples of 653 adult men, 400 girls, and 447 women were included in analyses. We applied exploratory factor analysis (EFA) to seven subcortical volumes in order to constrain the complexity of the input variables and ensure more stable clustering results. Factor scores derived from the EFA were used to build networks. A community detection (CD) algorithm clustered participants into subgroups based on the networks.ResultsExploratory factor analysis revealed three factors (basal ganglia, limbic system, and thalamus) in boys and men with and without ADHD. Factor structures for girls and women differed from those in males. Given sample size considerations, we concentrated subsequent analyses on males. Male participants could be separated into four communities, of which one was absent in healthy men. Significant case-control differences of subcortical volumes were observed within communities in boys, often with stronger effect sizes compared to the entire sample. As in the entire sample, none were observed in men. Affected men in two of the communities presented comorbidities more frequently than those in other communities. There were no significant differences in ADHD symptom severity, IQ, and medication use between communities in either boys or men.ConclusionsOur results indicate that neuroanatomic heterogeneity in subcortical volumes exists, irrespective of ADHD diagnosis. Effect sizes of case-control differences appear more pronounced at least in some of the subgroups.

Published
2021

29. ADHD medication discontinuation and persistence across the lifespan: a retrospective observational study using population-based databases

Author

Brikell, Isabell, Yao, Honghui, Li, Lin, Astrup, Aske, Gao, Le, Gillies, Malcolm B, Xie, Tian, Zhang-James, Yanli, Dalsgaard, Søren, Engeland, Anders, Faraone, Stephen V, Haavik, Jan, Hartman, Catharina, Ip, Patrick, Jakobsdóttir Smári, Unnur, Larsson, Henrik, Man, Kenneth KC, de Oliveira Costa, Juliana, Pearson, Sallie-Anne, Hostrup Nielsen, Nina Pil, Snieder, Harold, Wimberley, Theresa, Wong, Ian CK, Zhang, Le, Zoega, Helga, Klungsøyr, Kari, and Chang, Zheng

Published
2024
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32. Further Evidence of an Association Between a Positive Child Behavior Checklist-Bipolar Profile and a Diagnosis of Pediatric Bipolar Disorder: A Meta-Analysis

Author

DiSalvo Maura, Vater Chloe Hutt, Green Allison, Woodworth K. Yvonne, Farrell Abigail, Biederman Joseph, and Faraone Stephen

Subjects
bipolar disorder, cbcl, child behavior checklist, mood disorders, children, youth, Psychiatry, RC435-571, Psychology, BF1-990
Abstract

Previous research has found that a unique profile of the Child Behavior Checklist comprising of aggregate elevations of the Attention, Anxiety/Depression and Aggression scales (A-A-A profile, CBCL-Bipolar (BP) profile, CBCL-Dysregulation profile (DP); henceforth CBCL-BP/DP profile) is associated with a clinical diagnosis of pediatric bipolar (BP) disorder.

Published
2023
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33. Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders

Author

Radonjić, Nevena V, Hess, Jonathan L, Rovira, Paula, Andreassen, Ole, Buitelaar, Jan K, Ching, Christopher RK, Franke, Barbara, Hoogman, Martine, Jahanshad, Neda, McDonald, Carrie, Schmaal, Lianne, Sisodiya, Sanjay M, Stein, Dan J, van den Heuvel, Odile A, van Erp, Theo GM, van Rooij, Daan, Veltman, Dick J, Thompson, Paul, and Faraone, Stephen V

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Neurosciences, Serious Mental Illness, Genetics, Brain Disorders, Clinical Research, Autism, Intellectual and Developmental Disabilities (IDD), Schizophrenia, Mental Health, Prevention, Aetiology, 2.1 Biological and endogenous factors, Mental health, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Brain, Depressive Disorder, Major, Humans, Neuroimaging, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

Published
2021

34. Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits.

Author

Martin, Joanna, Khramtsova, Ekaterina A, Goleva, Slavina B, Blokland, Gabriëlla AM, Traglia, Michela, Walters, Raymond K, Hübel, Christopher, Coleman, Jonathan RI, Breen, Gerome, Børglum, Anders D, Demontis, Ditte, Grove, Jakob, Werge, Thomas, Bralten, Janita, Bulik, Cynthia M, Lee, Phil H, Mathews, Carol A, Peterson, Roseann E, Winham, Stacey J, Wray, Naomi, Edenberg, Howard J, Guo, Wei, Yao, Yin, Neale, Benjamin M, Faraone, Stephen V, Petryshen, Tracey L, Weiss, Lauren A, Duncan, Laramie E, Goldstein, Jill M, Smoller, Jordan W, Stranger, Barbara E, Davis, Lea K, and Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium

Subjects
Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium, Humans, Sex Characteristics, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Female, Male, Genome-Wide Association Study, Behavioral, GWAS, Genetic correlation, Heritability, Psychiatric, Sex differences, Prevention, Genetics, Mental Health, Human Genome, Biotechnology, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

BackgroundThe origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits.MethodsUsing European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (rg < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations.ResultsWe observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, although

Published
2021

35. Association between relative age at school and persistence of ADHD in prospective studies: an individual participant data meta-analysis

Author

Gosling, Corentin J, Caparos, Serge, Pinabiaux, Charlotte, Schwarzer, Guido, Rücker, Gerta, Agha, Sharifah S, Alrouh, Hekmat, Ambler, Antony, Anderson, Peter, Andiarena, Ainara, Arnold, L Eugene, Arseneault, Louise, Asherson, Philip, Babinski, Leslie, Barbati, Vittoria, Barkley, Russel, Barros, Aluisio J D, Barros, Fernando, Bates, John E, Bell, Laura J, Berenguer, Carmen, van Bergen, Elsje, Biederman, Joseph, Birmaher, Boris, B⊘e, Tormod, Boomsma, Dorret I, Brandt, Valerie C, Bressan, Rodrigo A, Brocki, Karin, Broughton, Thomas R, Bufferd, Sara J, Bussing, Regina, Cao, Meng, Cartigny, Ariane, Casas, Ana Miranda, Caspi, Avshalom, Castellanos, F Xavier, Caye, Arthur, Cederkvist, Luise, Collishaw, Stephan, Copeland, William E, Cote, Sylvana M, Coventry, William L, Debes, Nanette M.M. Mol, Denyer, Hayley, Dodge, Kenneth A, Dogru, Hicran, Efron, Daryl, Eller, Jami, Abd Elmaksoud, Marwa, Ercan, Eyup Sabri, Faraone, Stephen V, Fenesy, Michelle, Fernández, Mariana F, Fernández-Somoano, Ana, Findling, Robert, Fombonne, Eric, Fossum, Ingrid N, Freire, Carmen, Friedman, Naomi P, Fristad, Mary A, Galera, Cedric, Garcia-Argibay, Miguel, Garvan, Cynthia S, González-Safont, Llúcia, Groenman, Annabeth P, Guxens, Mònica, Halperin, Jeffrey M, Hamadeh, Randah R, Hartman, Catharina A, Hill, Shirley Y, Hinshaw, Stephen P, Hipwell, Alison, Hokkanen, Laura, Holz, Nathalie, Íñiguez, Carmen, Jahrami, Haitham A, Jansen, Pauline W, Jónsdóttir, Lilja K, Julvez, Jordi, Kaiser, Anna, Keenan, Kate, Klein, Daniel N, Klein, Rachel G, Kuntsi, Jonna, Langfus, Joshua, Langley, Kate, Lansford, Jennifer E, Larsen, Sally A, Larsson, Henrik, Law, Evelyn, Lee, Steve S, Lertxundi, Nerea, Li, Xiaobo, Li, Yueling, Lichtenstein, Paul, Liu, Jianghong, Lundervold, Astri J, Lundström, Sebastian, Marks, David J, Martin, Joanna, Masi, Gabriele, Matijasevich, Alicia, Melchior, Maria, Moffitt, Terrie E, Monninger, Maximilian, Morrison, Claire L, Mulraney, Melissa, Muratori, Pietro, Nguyen, Phuc T, Nicholson, Jan M, Øie, Merete Glenne, O'Neill, Sarah, O'Connor, Cliodhna, Orri, Massimiliano, Pan, Pedro M, Pascoe, Leona, Pettit, Gregory S, Price, Jolie, Rebagliato, Marisa, Riaño-Galán, Isolina, Rohde, Luis A, Roisman, Glenn I, Rosa, Maria, Rosenbaum, Jerrold F, Salum, Giovanni A, Sammallahti, Sara, Santos, Ina S, Schiavone, Nella S, Schmid, Lorrie, Sciberras, Emma, Shaw, Philip, Silk, Tim J, Simpson, Jeffry A, Skogli, Erik W, Stepp, Stephanie, Strandberg-Larsen, Katrine, Sudre, Gustavo, Sunyer, Jordi, Tandon, Mini, Thapar, Anita, Thomson, Phoebe, Thorell, Lisa B, Tinchant, Hannah, Torrent, Maties, Tovo-Rodrigues, Luciana, Tripp, Gail, Ukoumunne, Obioha, Van Goozen, Stephanie HM, Vos, Melissa, Wallez, Solène, Wang, Yufeng, Westermaier, Franz G, Whalen, Diana J, Yoncheva, Yuliya, Youngstrom, Eric A, Sayal, Kapil, Solmi, Marco, Delorme, Richard, and Cortese, Samuele

Published
2023
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36. A polygenic resilience score moderates the genetic risk for schizophrenia

Author

Hess, Jonathan L, Tylee, Daniel S, Mattheisen, Manuel, Børglum, Anders D, Als, Thomas D, Grove, Jakob, Werge, Thomas, Mortensen, Preben Bo, Mors, Ole, Nordentoft, Merete, Hougaard, David M, Byberg-Grauholm, Jonas, Bækvad-Hansen, Marie, Greenwood, Tiffany A, Tsuang, Ming T, Curtis, David, Steinberg, Stacy, Sigurdsson, Engilbert, Stefánsson, Hreinn, Stefánsson, Kári, Edenberg, Howard J, Holmans, Peter, Faraone, Stephen V, and Glatt, Stephen J

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical and Health Psychology, Clinical Sciences, Psychology, Schizophrenia, Serious Mental Illness, Genetics, Mental Health, Brain Disorders, Prevention, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Alleles, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Risk Factors, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Lundbeck Foundation Initiative for Integrative Psychiatric Research, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531-538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known "polygenic resilience score" that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.

Published
2021

37. Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

Author

Zhang-James, Yanli, Helminen, Emily C, Liu, Jinru, Franke, Barbara, Hoogman, Martine, and Faraone, Stephen V

Subjects
Biological Psychology, Psychology, Pediatric, Mental Health, Neurosciences, Behavioral and Social Science, Brain Disorders, Attention Deficit Hyperactivity Disorder (ADHD), 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Brain, Child, Humans, Machine Learning, Magnetic Resonance Imaging, Young Adult, ENIGMA-ADHD Working Group, Clinical Sciences, Public Health and Health Services, Clinical sciences, Biological psychology
Abstract

Attention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD's brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity.

Published
2021

39. Anxiety, mood, and substance use disorders in adult men and women with and without attention-deficit/hyperactivity disorder: A substantive and methodological overview

Author

Hartman, Catharina A., Larsson, Henrik, Vos, Melissa, Bellato, Alessio, Libutzki, Berit, Solberg, Berit Skretting, Chen, Qi, Du Rietz, Ebba, Mostert, Jeanette C., Kittel-Schneider, Sarah, Cormand, Bru, Ribasés, Marta, Klungsøyr, Kari, Haavik, Jan, Dalsgaard, Søren, Cortese, Samuele, Faraone, Stephen V., and Reif, Andreas

Published
2023
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40. Risk variants and polygenic architecture of disruptive behavior disorders in the context of attention-deficit/hyperactivity disorder.

Author

Demontis, Ditte, Walters, Raymond K, Rajagopal, Veera M, Waldman, Irwin D, Grove, Jakob, Als, Thomas D, Dalsgaard, Søren, Ribasés, Marta, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Maria, Werge, Thomas, Nordentoft, Merete, Mors, Ole, Mortensen, Preben Bo, ADHD Working Group of the Psychiatric Genomics Consortium (PGC), Cormand, Bru, Hougaard, David M, Neale, Benjamin M, Franke, Barbara, Faraone, Stephen V, and Børglum, Anders D

Subjects
ADHD Working Group of the Psychiatric Genomics Consortium, Humans, Genetic Predisposition to Disease, Risk Factors, Cohort Studies, Attention Deficit and Disruptive Behavior Disorders, Attention Deficit Disorder with Hyperactivity, Comorbidity, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Child, China, Europe, Female, Male, Genome-Wide Association Study, Violence Research, Prevention, Pediatric, Genetics, Attention Deficit Disorder (ADD), Brain Disorders, Mental Health, Human Genome, Behavioral and Social Science, 2.1 Biological and endogenous factors, Mental health
Abstract

Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood psychiatric disorder often comorbid with disruptive behavior disorders (DBDs). Here, we report a GWAS meta-analysis of ADHD comorbid with DBDs (ADHD + DBDs) including 3802 cases and 31,305 controls. We identify three genome-wide significant loci on chromosomes 1, 7, and 11. A meta-analysis including a Chinese cohort supports that the locus on chromosome 11 is a strong risk locus for ADHD + DBDs across European and Chinese ancestries (rs7118422, P = 3.15×10-10, OR = 1.17). We find a higher SNP heritability for ADHD + DBDs (h2SNP = 0.34) when compared to ADHD without DBDs (h2SNP = 0.20), high genetic correlations between ADHD + DBDs and aggressive (rg = 0.81) and anti-social behaviors (rg = 0.82), and an increased burden (polygenic score) of variants associated with ADHD and aggression in ADHD + DBDs compared to ADHD without DBDs. Our results suggest an increased load of common risk variants in ADHD + DBDs compared to ADHD without DBDs, which in part can be explained by variants associated with aggressive behavior.

Published
2021

43. Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis

Author

Tielbeek, Jorim J., Uffelmann, Emil, Williams, Benjamin S., Colodro-Conde, Lucía, Gagnon, Éloi, Mallard, Travis T., Levitt, Brandt E., Jansen, Philip R., Johansson, Ada, Sallis, Hannah M., Pistis, Giorgio, Saunders, Gretchen R. B., Allegrini, Andrea G., Rimfeld, Kaili, Konte, Bettina, Klein, Marieke, Hartmann, Annette M., Salvatore, Jessica E., Nolte, Ilja M., Demontis, Ditte, Malmberg, Anni L. K., Burt, S. Alexandra, Savage, Jeanne E., Sugden, Karen, Poulton, Richie, Harris, Kathleen Mullan, Vrieze, Scott, McGue, Matt, Iacono, William G., Mota, Nina Roth, Mill, Jonathan, Viana, Joana F., Mitchell, Brittany L., Morosoli, Jose J., Andlauer, Till F. M., Ouellet-Morin, Isabelle, Tremblay, Richard E., Côté, Sylvana M., Gouin, Jean-Philippe, Brendgen, Mara R., Dionne, Ginette, Vitaro, Frank, Lupton, Michelle K., Martin, Nicholas G., Castelao, Enrique, Räikkönen, Katri, Eriksson, Johan G., Lahti, Jari, Hartman, Catharina A., Oldehinkel, Albertine J., Snieder, Harold, Liu, Hexuan, Preisig, Martin, Whipp, Alyce, Vuoksimaa, Eero, Lu, Yi, Jern, Patrick, Rujescu, Dan, Giegling, Ina, Palviainen, Teemu, Kaprio, Jaakko, Harden, Kathryn Paige, Munafò, Marcus R., Morneau-Vaillancourt, Geneviève, Plomin, Robert, Viding, Essi, Boutwell, Brian B., Aliev, Fazil, Dick, Danielle M., Popma, Arne, Faraone, Stephen V., Børglum, Anders D., Medland, Sarah E., Franke, Barbara, Boivin, Michel, Pingault, Jean-Baptiste, Glennon, Jeffrey C., Barnes, J. C., Fisher, Simon E., Moffitt, Terrie E., Caspi, Avshalom, Polderman, Tinca J. C., and Posthuma, Danielle

Published
2022
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45. Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups

Author

Boedhoe, Premika SW, van Rooij, Daan, Hoogman, Martine, Twisk, Jos WR, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anikin, Anatoly, Anticevic, Alan, Arango, Celso, Arnold, Paul D, Asherson, Philip, Assogna, Francesca, Auzias, Guillaume, Banaschewski, Tobias, Baranov, Alexander, Batistuzzo, Marcelo C, Baumeister, Sarah, Baur-Streubel, Ramona, Behrmann, Marlene, Bellgrove, Mark A, Benedetti, Francesco, Beucke, Jan C, Biederman, Joseph, Bollettini, Irene, Bose, Anushree, Bralten, Janita, Bramati, Ivanei E, Brandeis, Daniel, Brem, Silvia, Brennan, Brian P, Busatto, Geraldo F, Calderoni, Sara, Calvo, Anna, Calvo, Rosa, Castellanos, Francisco X, Cercignani, Mara, Chaim-Avancini, Tiffany M, Chantiluke, Kaylita C, Cheng, Yuqi, Cho, Kang Ik K, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Cubillo, Ana I, Dale, Anders M, Dallaspezia, Sara, Daly, Eileen, Denys, Damiaan, Deruelle, Christine, Di Martino, Adriana, Dinstein, Ilan, Doyle, Alysa E, Durston, Sarah, Earl, Eric A, Ecker, Christine, Ehrlich, Stefan, Ely, Benjamin A, Epstein, Jeffrey N, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas J, Faraone, Stephen V, Fedor, Jennifer, Feng, Xin, Feusner, Jamie D, Fitzgerald, Jackie, Fitzgerald, Kate D, Fouche, Jean-Paul, Freitag, Christine M, Fridgeirsson, Egill A, Frodl, Thomas, Gabel, Matt C, Gallagher, Louise, Gogberashvili, Tinatin, Gori, Ilaria, Gruner, Patricia, Gürsel, Deniz A, Haar, Shlomi, Haavik, Jan, Hall, Geoffrey B, Harrison, Neil A, Hartman, Catharina A, Heslenfeld, Dirk J, Hirano, Yoshiyuki, Hoekstra, Pieter J, Hoexter, Marcelo Q, Hohmann, Sarah, Høvik, Marie F, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, Jalbrzikowski, Maria, James, Anthony, Janssen, Joost, Jaspers-Fayer, Fern, Jernigan, Terry L, Kapilushniy, Dmitry, and Kardatzki, Bernd

Subjects
Attention Deficit Hyperactivity Disorder (ADHD), Behavioral and Social Science, Clinical Research, Mental Health, Neurosciences, Pediatric, Autism, Intellectual and Developmental Disabilities (IDD), Brain Disorders, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Neurological, Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Cerebrum, Child, Female, Human Development, Humans, Male, Neuroimaging, Obsessive-Compulsive Disorder, Organ Size, Psychopathology, Research Report, Systems Analysis, ENIGMA ADHD working group, ENIGMA ASD working group, ENIGMA OCD working group, Attention Deficit Hyperactivity Disorder, ENIGMA, Structural MRI, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

ObjectiveAttention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.MethodsStructural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).ResultsNo shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.ConclusionsThe study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Published
2020

46. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

Author

Thompson, Paul M, Jahanshad, Neda, Ching, Christopher RK, Salminen, Lauren E, Thomopoulos, Sophia I, Bright, Joanna, Baune, Bernhard T, Bertolín, Sara, Bralten, Janita, Bruin, Willem B, Bülow, Robin, Chen, Jian, Chye, Yann, Dannlowski, Udo, de Kovel, Carolien GF, Donohoe, Gary, Eyler, Lisa T, Faraone, Stephen V, Favre, Pauline, Filippi, Courtney A, Frodl, Thomas, Garijo, Daniel, Gil, Yolanda, Grabe, Hans J, Grasby, Katrina L, Hajek, Tomas, Han, Laura KM, Hatton, Sean N, Hilbert, Kevin, Ho, Tiffany C, Holleran, Laurena, Homuth, Georg, Hosten, Norbert, Houenou, Josselin, Ivanov, Iliyan, Jia, Tianye, Kelly, Sinead, Klein, Marieke, Kwon, Jun Soo, Laansma, Max A, Leerssen, Jeanne, Lueken, Ulrike, Nunes, Abraham, Neill, Joseph O', Opel, Nils, Piras, Fabrizio, Piras, Federica, Postema, Merel C, Pozzi, Elena, Shatokhina, Natalia, Soriano-Mas, Carles, Spalletta, Gianfranco, Sun, Daqiang, Teumer, Alexander, Tilot, Amanda K, Tozzi, Leonardo, van der Merwe, Celia, Van Someren, Eus JW, van Wingen, Guido A, Völzke, Henry, Walton, Esther, Wang, Lei, Winkler, Anderson M, Wittfeld, Katharina, Wright, Margaret J, Yun, Je-Yeon, Zhang, Guohao, Zhang-James, Yanli, Adhikari, Bhim M, Agartz, Ingrid, Aghajani, Moji, Aleman, André, Althoff, Robert R, Altmann, Andre, Andreassen, Ole A, Baron, David A, Bartnik-Olson, Brenda L, Marie Bas-Hoogendam, Janna, Baskin-Sommers, Arielle R, Bearden, Carrie E, Berner, Laura A, Boedhoe, Premika SW, Brouwer, Rachel M, Buitelaar, Jan K, Caeyenberghs, Karen, Cecil, Charlotte AM, Cohen, Ronald A, Cole, James H, Conrod, Patricia J, De Brito, Stephane A, de Zwarte, Sonja MC, Dennis, Emily L, Desrivieres, Sylvane, Dima, Danai, Ehrlich, Stefan, Esopenko, Carrie, Fairchild, Graeme, Fisher, Simon E, Fouche, Jean-Paul, and Francks, Clyde

Subjects
ENIGMA Consortium, Brain, Humans, Magnetic Resonance Imaging, Reproducibility of Results, Depressive Disorder, Major, Neuroimaging, Neurosciences, Clinical Research, Mental Health, Brain Disorders, Behavioral and Social Science, Genetics, Basic Behavioral and Social Science, Prevention, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Mental health, Neurological, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Published
2020

47. Exome sequencing in schizophrenia-affected parent–offspring trios reveals risk conferred by protein-coding de novo mutations

Author

Howrigan, Daniel P, Rose, Samuel A, Samocha, Kaitlin E, Fromer, Menachem, Cerrato, Felecia, Chen, Wei J, Churchhouse, Claire, Chambert, Kimberly, Chandler, Sharon D, Daly, Mark J, Dumont, Ashley, Genovese, Giulio, Hwu, Hai-Gwo, Laird, Nan, Kosmicki, Jack A, Moran, Jennifer L, Roe, Cheryl, Singh, Tarjinder, Wang, Shi-Heng, Faraone, Stephen V, Glatt, Stephen J, McCarroll, Steven A, Tsuang, Ming, and Neale, Benjamin M

Subjects
Serious Mental Illness, Schizophrenia, Mental Health, Biotechnology, Human Genome, Clinical Research, Genetics, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Adult, Child, Family, Female, Genetic Predisposition to Disease, Humans, Male, Mutation, Parents, Exome Sequencing, Neurosciences, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Protein-coding de novo mutations (DNMs) are significant risk factors in many neurodevelopmental disorders, whereas schizophrenia (SCZ) risk associated with DNMs has thus far been shown to be modest. We analyzed DNMs from 1,695 SCZ-affected trios and 1,077 published SCZ-affected trios to better understand the contribution to SCZ risk. Among 2,772 SCZ probands, exome-wide DNM burden remained modest. Gene set analyses revealed that SCZ DNMs were significantly concentrated in genes that were highly expressed in the brain, that were under strong evolutionary constraint and/or overlapped with genes identified in other neurodevelopmental disorders. No single gene surpassed exome-wide significance; however, 16 genes were recurrently hit by protein-truncating DNMs, corresponding to a 3.15-fold higher rate than the mutation model expectation (permuted 95% confidence interval: 1-10 genes; permuted P = 3 × 10-5). Overall, DNMs explain a small fraction of SCZ risk, and larger samples are needed to identify individual risk genes, as coding variation across many genes confers risk for SCZ in the population.

Published
2020

48. Comparative genetic architectures of schizophrenia in East Asian and European populations

Author

Lam, Max, Chen, Chia-Yen, Li, Zhiqiang, Martin, Alicia R, Bryois, Julien, Ma, Xixian, Gaspar, Helena, Ikeda, Masashi, Benyamin, Beben, Brown, Brielin C, Liu, Ruize, Zhou, Wei, Guan, Lili, Kamatani, Yoichiro, Kim, Sung-Wan, Kubo, Michiaki, Kusumawardhani, Agung AAA, Liu, Chih-Min, Ma, Hong, Periyasamy, Sathish, Takahashi, Atsushi, Xu, Zhida, Yu, Hao, Zhu, Feng, Chen, Wei J, Faraone, Stephen, Glatt, Stephen J, He, Lin, Hyman, Steven E, Hwu, Hai-Gwo, McCarroll, Steven A, Neale, Benjamin M, Sklar, Pamela, Wildenauer, Dieter B, Yu, Xin, Zhang, Dai, Mowry, Bryan J, Lee, Jimmy, Holmans, Peter, Xu, Shuhua, Sullivan, Patrick F, Ripke, Stephan, O’Donovan, Michael C, Daly, Mark J, Qin, Shengying, Sham, Pak, Iwata, Nakao, Hong, Kyung S, Schwab, Sibylle G, Yue, Weihua, Tsuang, Ming, Liu, Jianjun, Ma, Xiancang, Kahn, René S, Shi, Yongyong, and Huang, Hailiang

Subjects
Genetics, Human Genome, Serious Mental Illness, Schizophrenia, Brain Disorders, Mental Health, Prevention, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Asian People, Case-Control Studies, Asia, Eastern, Genetics, Population, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, White People, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Indonesia Schizophrenia Consortium, Genetic REsearch on schizophreniA neTwork-China and the Netherlands, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations.

Published
2019

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