Browsing by Author "Liberzon, Israel"

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    ItemOpen Access
    International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.
    (Nature communications, 2019-10) Nievergelt, Caroline M; Maihofer, Adam X; Klengel, Torsten; Atkinson, Elizabeth G; Chen, Chia-Yen; Choi, Karmel W; Coleman, Jonathan RI; Dalvie, Shareefa; Duncan, Laramie E; Gelernter, Joel; Levey, Daniel F; Logue, Mark W; Polimanti, Renato; Provost, Allison C; Ratanatharathorn, Andrew; Stein, Murray B; Torres, Katy; Aiello, Allison E; Almli, Lynn M; Amstadter, Ananda B; Andersen, Søren B; Andreassen, Ole A; Arbisi, Paul A; Ashley-Koch, Allison E; Austin, S Bryn; Avdibegovic, Esmina; Babić, Dragan; Bækvad-Hansen, Marie; Baker, Dewleen G; Beckham, Jean C; Bierut, Laura J; Bisson, Jonathan I; Boks, Marco P; Bolger, Elizabeth A; Børglum, Anders D; Bradley, Bekh; Brashear, Megan; Breen, Gerome; Bryant, Richard A; Bustamante, Angela C; Bybjerg-Grauholm, Jonas; Calabrese, Joseph R; Caldas-de-Almeida, José M; Dale, Anders M; Daly, Mark J; Daskalakis, Nikolaos P; Deckert, Jürgen; Delahanty, Douglas L; Dennis, Michelle F; Disner, Seth G; Domschke, Katharina; Dzubur-Kulenovic, Alma; Erbes, Christopher R; Evans, Alexandra; Farrer, Lindsay A; Feeny, Norah C; Flory, Janine D; Forbes, David; Franz, Carol E; Galea, Sandro; Garrett, Melanie E; Gelaye, Bizu; Geuze, Elbert; Gillespie, Charles; Uka, Aferdita Goci; Gordon, Scott D; Guffanti, Guia; Hammamieh, Rasha; Harnal, Supriya; Hauser, Michael A; Heath, Andrew C; Hemmings, Sian MJ; Hougaard, David Michael; Jakovljevic, Miro; Jett, Marti; Johnson, Eric Otto; Jones, Ian; Jovanovic, Tanja; Qin, Xue-Jun; Junglen, Angela G; Karstoft, Karen-Inge; Kaufman, Milissa L; Kessler, Ronald C; Khan, Alaptagin; Kimbrel, Nathan A; King, Anthony P; Koen, Nastassja; Kranzler, Henry R; Kremen, William S; Lawford, Bruce R; Lebois, Lauren AM; Lewis, Catrin E; Linnstaedt, Sarah D; Lori, Adriana; Lugonja, Bozo; Luykx, Jurjen J; Lyons, Michael J; Maples-Keller, Jessica; Marmar, Charles; Martin, Alicia R; Martin, Nicholas G; Maurer, Douglas; Mavissakalian, Matig R; McFarlane, Alexander; McGlinchey, Regina E; McLaughlin, Katie A; McLean, Samuel A; McLeay, Sarah; Mehta, Divya; Milberg, William P; Miller, Mark W; Morey, Rajendra A; Morris, Charles Phillip; Mors, Ole; Mortensen, Preben B; Neale, Benjamin M; Nelson, Elliot C; Nordentoft, Merete; Norman, Sonya B; O'Donnell, Meaghan; Orcutt, Holly K; Panizzon, Matthew S; Peters, Edward S; Peterson, Alan L; Peverill, Matthew; Pietrzak, Robert H; Polusny, Melissa A; Rice, John P; Ripke, Stephan; Risbrough, Victoria B; Roberts, Andrea L; Rothbaum, Alex O; Rothbaum, Barbara O; Roy-Byrne, Peter; Ruggiero, Ken; Rung, Ariane; Rutten, Bart PF; Saccone, Nancy L; Sanchez, Sixto E; Schijven, Dick; Seedat, Soraya; Seligowski, Antonia V; Seng, Julia S; Sheerin, Christina M; Silove, Derrick; Smith, Alicia K; Smoller, Jordan W; Sponheim, Scott R; Stein, Dan J; Stevens, Jennifer S; Sumner, Jennifer A; Teicher, Martin H; Thompson, Wesley K; Trapido, Edward; Uddin, Monica; Ursano, Robert J; van den Heuvel, Leigh Luella; Van Hooff, Miranda; Vermetten, Eric; Vinkers, Christiaan H; Voisey, Joanne; Wang, Yunpeng; Wang, Zhewu; Werge, Thomas; Williams, Michelle A; Williamson, Douglas E; Winternitz, Sherry; Wolf, Christiane; Wolf, Erika J; Wolff, Jonathan D; Yehuda, Rachel; Young, Ross McD; Young, Keith A; Zhao, Hongyu; Zoellner, Lori A; Liberzon, Israel; Ressler, Kerry J; Haas, Magali; Koenen, Karestan C
    The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.
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    ItemOpen Access
    Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.
    (NeuroImage, 2023-12) Zhu, Xi; Kim, Yoojean; Ravid, Orren; He, Xiaofu; Suarez-Jimenez, Benjamin; Zilcha-Mano, Sigal; Lazarov, Amit; Lee, Seonjoo; Abdallah, Chadi G; Angstadt, Michael; Averill, Christopher L; Baird, C Lexi; Baugh, Lee A; Blackford, Jennifer U; Bomyea, Jessica; Bruce, Steven E; Bryant, Richard A; Cao, Zhihong; Choi, Kyle; Cisler, Josh; Cotton, Andrew S; Daniels, Judith K; Davenport, Nicholas D; Davidson, Richard J; DeBellis, Michael D; Dennis, Emily L; Densmore, Maria; deRoon-Cassini, Terri; Disner, Seth G; Hage, Wissam El; Etkin, Amit; Fani, Negar; Fercho, Kelene A; Fitzgerald, Jacklynn; Forster, Gina L; Frijling, Jessie L; Geuze, Elbert; Gonenc, Atilla; Gordon, Evan M; Gruber, Staci; Grupe, Daniel W; Guenette, Jeffrey P; Haswell, Courtney C; Herringa, Ryan J; Herzog, Julia; Hofmann, David Bernd; Hosseini, Bobak; Hudson, Anna R; Huggins, Ashley A; Ipser, Jonathan C; Jahanshad, Neda; Jia-Richards, Meilin; Jovanovic, Tanja; Kaufman, Milissa L; Kennis, Mitzy; King, Anthony; Kinzel, Philipp; Koch, Saskia BJ; Koerte, Inga K; Koopowitz, Sheri M; Korgaonkar, Mayuresh S; Krystal, John H; Lanius, Ruth; Larson, Christine L; Lebois, Lauren AM; Li, Gen; Liberzon, Israel; Lu, Guang Ming; Luo, Yifeng; Magnotta, Vincent A; Manthey, Antje; Maron-Katz, Adi; May, Geoffery; McLaughlin, Katie; Mueller, Sven C; Nawijn, Laura; Nelson, Steven M; Neufeld, Richard WJ; Nitschke, Jack B; O'Leary, Erin M; Olatunji, Bunmi O; Olff, Miranda; Peverill, Matthew; Phan, K Luan; Qi, Rongfeng; Quidé, Yann; Rektor, Ivan; Ressler, Kerry; Riha, Pavel; Ross, Marisa; Rosso, Isabelle M; Salminen, Lauren E; Sambrook, Kelly; Schmahl, Christian; Shenton, Martha E; Sheridan, Margaret; Shih, Chiahao; Sicorello, Maurizio; Sierk, Anika; Simmons, Alan N; Simons, Raluca M; Simons, Jeffrey S; Sponheim, Scott R; Stein, Murray B; Stein, Dan J; Stevens, Jennifer S; Straube, Thomas; Sun, Delin; Théberge, Jean; Thompson, Paul M; Thomopoulos, Sophia I; van der Wee, Nic JA; van der Werff, Steven JA; van Erp, Theo GM; van Rooij, Sanne JH; van Zuiden, Mirjam; Varkevisser, Tim; Veltman, Dick J; Vermeiren, Robert RJM; Walter, Henrik; Wang, Li; Wang, Xin; Weis, Carissa; Winternitz, Sherry; Xie, Hong; Zhu, Ye; Wall, Melanie; Neria, Yuval; Morey, Rajendra A

    Background

    Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.

    Methods

    We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.

    Results

    We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.

    Conclusion

    These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.
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    ItemOpen Access
    The Psychiatric Genomics Consortium Posttraumatic Stress Disorder Workgroup: Posttraumatic Stress Disorder Enters the Age of Large-Scale Genomic Collaboration.
    (Neuropsychopharmacology, 2015-09) Logue, Mark W; Amstadter, Ananda B; Baker, Dewleen G; Duncan, Laramie; Koenen, Karestan C; Liberzon, Israel; Miller, Mark W; Morey, Rajendra A; Nievergelt, Caroline M; Ressler, Kerry J; Smith, Alicia K; Smoller, Jordan W; Stein, Murray B; Sumner, Jennifer A; Uddin, Monica
    The development of posttraumatic stress disorder (PTSD) is influenced by genetic factors. Although there have been some replicated candidates, the identification of risk variants for PTSD has lagged behind genetic research of other psychiatric disorders such as schizophrenia, autism, and bipolar disorder. Psychiatric genetics has moved beyond examination of specific candidate genes in favor of the genome-wide association study (GWAS) strategy of very large numbers of samples, which allows for the discovery of previously unsuspected genes and molecular pathways. The successes of genetic studies of schizophrenia and bipolar disorder have been aided by the formation of a large-scale GWAS consortium: the Psychiatric Genomics Consortium (PGC). In contrast, only a handful of GWAS of PTSD have appeared in the literature to date. Here we describe the formation of a group dedicated to large-scale study of PTSD genetics: the PGC-PTSD. The PGC-PTSD faces challenges related to the contingency on trauma exposure and the large degree of ancestral genetic diversity within and across participating studies. Using the PGC analysis pipeline supplemented by analyses tailored to address these challenges, we anticipate that our first large-scale GWAS of PTSD will comprise over 10 000 cases and 30 000 trauma-exposed controls. Following in the footsteps of our PGC forerunners, this collaboration-of a scope that is unprecedented in the field of traumatic stress-will lead the search for replicable genetic associations and new insights into the biological underpinnings of PTSD.