6 results on '"Anthony O'Neill F"'
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2. Proof of concept: Molecular prediction of schizophrenia risk
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Anthony O’Neill F, Kenneth S. Kendler, P.F. Sullivan, Gaurav Kumar, Silviu-Alin Bacanu, Ayman H. Fanous, Anna R. Docherty, Gemma T. Wallace, Daniel E. Adkins, Arden Moscati, Brien P. Riley, Corvin A, and M. Gill
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Genetics ,0303 health sciences ,education.field_of_study ,Psychosis ,biology ,Population ,Genomics ,Recursive partitioning ,Stepwise regression ,Major histocompatibility complex ,medicine.disease ,Bioinformatics ,Odds ,03 medical and health sciences ,0302 clinical medicine ,Cohort ,biology.protein ,medicine ,education ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
Key PointsQuestionTo what extent do global polygenic risk scores (PRS), molecular pathway-specific PRS, complement component (C4) gene expression, MHC loci, sex, and ancestry jointly contribute to risk for schizophrenia-spectrum disorders (SZ)?FindingsGlobal polygenic risk for schizophrenia, sex, and their interaction most robustly predict risk in a classification and regression tree model, with highest risk groups having 50/50 chance of SZ.MeaningPsychometric risk indicators, such as prodromal symptom assessments, may be enhanced by the examination of genetic risk metrics. Preliminary results suggest that of genetic risk metrics, global polygenic information has the most potential to significantly aide in the prediction of SZ.AbstractImportanceSchizophrenia (SZ) has a complex, heterogeneous symptom presentation with limited established associations between biological markers and illness onset. Many (gene) molecular pathways (MPs) are enriched for SZ signal, but it is still unclear how these MPs, global PRS, major histocompatibility complex (MHC) complement component (C4) gene expression, and MHC loci might jointly contribute to SZ and its clinical presentation. It is also unclear whether sex or ancestry interacts with these metrics to increase risk in certain individuals.ObjectiveTo examine multiple genetic metrics, sex, and their interactions as possible predictors of SZ risk. Genetic information could aid in the clinical prediction of risk, but it is still unclear which genetic metrics are most promising, and how sex interacts with genetic risk metrics.Design, Setting, and ParticipantsTo examine molecular risk in a proof-of-concept study, we used the Wellcome Trust case-control cohort and classified cases as a function of 1) polygenic risk score (PRS) for both whole genome and for 345 implicated molecular pathways, 2) predicted C4 expression, 3) SZ-relevant MHC loci, 4) sex, and 5) ancestry.Main Outcomes and MeasuresPRSs, C4 expression, SZ-relevant MHC loci, sex, and ancestry as joint risk factors for SZ.ResultsRecursive partitioning yielded 15 molecular risk classes and retained as significant psychosis classifiers only sex, genome-wide SZ polygenic risk, and one MP PRS. Sex was the most robust classifier in a stepwise regression, and there was a significant interaction of sex with SZ PRS on case status, suggesting males have a lower polygenic risk threshold. By down-sampling case proportion to 1% and 1.4% population base rates in males and females, respectively, high-risk subtypes defined by this model had roughly a 52% odds of developing SZ (individuals with SZ PRS elevated by 2.6 SDs; incidence = 51.8%).Conclusions and RelevanceThis proof-of-concept suggests that global SZ PRS, sex, and their interaction are robust predictors of risk and that males have a lower PRS threshold for onset. Implications for the integration of these metrics with psychometrically-identified risk are discussed.
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- 2017
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3. No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study
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Johnson, Emma C., Bjelland, Douglas W., Howrigan, Daniel P., Abdellaoui, Abdel, Breen, Gerome, Borglum, Anders, Cichon, Sven, Degenhardt, Franziska, Forstner, Andreas J., Frank, Josef, Genovese, Giulio, Heilmann-Heimbach, Stefanie, Herms, Stefan, Hoffman, Per, Maier, Wolfgang, Mattheisen, Manuel, Morris, Derek, Mowry, Bryan, Müller-Mhysok, Betram, Neale, Benjamin, Nenadic, Igor, Nöthen, Markus M., O’Dushlaine, Colm, Rietschel, Marcella, Ruderfer, Douglas M., Rujescu, Dan, Schulze, Thomas G., Simonson, Matthew A., Stahl, Eli, Strohmaier, Jana, Witt, Stephanie H., Ripke, Stephan, Neale, Benjamin M., Corvin, Aiden, Walters, James T R, Farh, Kai How, Holmans, Peter A., Lee, Phil, Bulik-Sullivan, Brendan, Collier, David A., Huang, Hailiang, Pers, Tune H., Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A., Begemann, Martin, Belliveau, Richard A., Bene, Judit, Bergen, Sarah E., Bevilacqua, Elizabeth, Bigdeli, Tim B., Black, Donald W., Bruggeman, Richard, Buccola, Nancy G., Buckner, Randy L., Byerley, William, Cahn, Wiepke, Cai, Guiqing, Campion, Dominique, Cantor, Rita M., Carr, Vaughan J., Carrera, Noa, Catts, Stanley V., Chambert, Kimberly D., Chan, Raymond C K, Chen, Ronald Y L, Chen, Eric Y H, Cheng, Wei, Cheung, Eric F C, Chong, Siow Ann, Robert Cloninger, C., Cohen, David, Cohen, Nadine, Cormican, Paul, Craddock, Nick, Crowley, James J., Curtis, David, Davidson, Michael, Davis, Kenneth L., Del Favero, Jurgen, Demontis, Ditte, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Donohoe, Gary, Drapeau, Elodie, Duan, Jubao, Dudbridge, Frank, Durmishi, Naser, Eichhammer, Peter, Eriksson, Johan, Escott-Price, Valentina, Essioux, Laurent, Fanous, Ayman H., Farrell, Martilias S., Franke, Lude, Freedman, Robert, Freimer, Nelson B., Friedl, Marion, Friedman, Joseph I., Fromer, Menachem, Georgieva, Lyudmila, Giegling, Ina, Giusti-Rodríguez, Paola, Godard, Stephanie, Goldstein, Jacqueline I., Golimbet, Vera, Gopal, Srihari, Gratten, Jacob, de Haan, Lieuwe, Hammer, Christian, Hamshere, Marian L., Hansen, Mark, Hansen, Thomas, Haroutunian, Vahram, Hartmann, Annette M., Henskens, Frans A., Hirschhorn, Joel N., Hoffmann, Per, Hofman, Andrea, Hollegaard, Mads V., Hougaard, David M., Ikeda, Masashi, Joa, Inge, Julià, Antonio, Kahn, René S., Kalaydjieva, Luba, Karachanak-Yankova, Sena, Karjalainen, Juha, Kavanagh, David, Kennedy, James L., Khrunin, Andrey, Kim, Yunjung, Klovins, Janis, Knowles, James A., Konte, Bettina, Kucinskas, Vaidutis, Kucinskiene, Zita Ausrele, Kuzelova-Ptackova, Hana, Kähler, Anna K., Laurent, Claudine, Chee Keong, Jimmy Lee, Hong Lee, S., Legge, Sophie E., Lerer, Bernard, Li, Miaoxin, Li, Tao, Liang, Kung Yee, Lieberman, Jeffrey, Limborska, Svetlana, Loughland, Carmel M., Lubinski, Jan, Lönnqvist, Jouko, Macek, Milan, Magnusson, Patrik K E, Maher, Brion S., Mallet, Jacques, Marsal, Sara, Mattingsdal, Morten, McCarley, Robert W., McDonald, Colm, McIntosh, Andrew M., Meier, Sandra, Meijer, Carin J., Melegh, Bela, Melle, Ingrid, Mesholam-Gately, Raquelle I., Metspalu, Andres, Michie, Patricia T., Milani, Lili, Milanova, Vihra, Mokrab, Younes, Morris, Derek W., Mors, Ole, Murphy, Kieran C., Murray, Robin M., Myin-Germeys, Inez, Müller-Myhsok, Bertram, Nelis, Mari, Nertney, Deborah A., Nestadt, Gerald, Nicodemus, Kristin K., Nikitina-Zake, Liene, Nisenbaum, Laura, Nordin, Annelie, O'Callaghan, Eadbhard, O'Dushlaine, Colm, Anthony O'Neill, F., Oh, Sang Yun, Olincy, Ann, Olsen, Line, Van Os, Jim, Pantelis, Christos, Papadimitriou, George N., Papiol, Sergi, Parkhomenko, Elena, Pato, Michele T., Paunio, Tiina, Pejovic-Milovancevic, Milica, Perkins, Diana O., Pietiläinen, Olli, Pimm, Jonathan, Pocklington, Andrew J., Powell, John, Price, Alkes, Pulver, Ann E., Purcell, Shaun M., Quested, Digby, Rasmussen, Henrik B., Reichenberg, Abraham, Reimers, Mark A., Richards, Alexander L., Roffman, Joshua L., Roussos, Panos, Salomaa, Veikko, Sanders, Alan R., Schall, Ulrich, Schubert, Christian R., Schwab, Sibylle G., Scolnick, Edward M., Scott, Rodney J., Seidman, Larry J., Shi, Jianxin, Sigurdsson, Engilbert, Silagadze, Teimuraz, Silverman, Jeremy M., Sim, Kang, Slominsky, Petr, Smoller, Jordan W., So, Hon Cheong, Spencer, Chris C A, Stahl, Eli A., Stefansson, Hreinn, Steinberg, Stacy, Stogmann, Elisabeth, Straub, Richard E., Strengman, Eric, Scott Stroup, T., Subramaniam, Mythily, Suvisaari, Jaana, Svrakic, Dragan M., Szatkiewicz, Jin P., Söderman, Erik, Thirumalai, Srinivas, Toncheva, Draga, Tosato, Sarah, Veijola, Juha, Waddington, John, Walsh, Dermot, Wang, Dai, Wang, Qiang, Webb, Bradley T., Weiser, Mark, Wildenauer, Dieter B., Williams, Nigel M., Williams, Stephanie, Wolen, Aaron R., Wong, Emily H M, Wormley, Brandon K., Xi, Hualin Simon, Zai, Clement C., Zheng, Xuebin, Zimprich, Fritz, Wray, Naomi R., Stefansson, Kari, Visscher, Peter M., Adolfsson, Rolf, Andreassen, Ole A., Blackwood, Douglas H R, Bramon, Elvira, Buxbaum, Joseph D., Børglum, Anders D., Darvasi, Ariel, Domenici, Enrico, Ehrenreich, Hannelore, Esko, Tõnu, Gejman, Pablo V., Gill, Michael, Gurling, Hugh, Hultman, Christina M., Iwata, Nakao, Jablensky, Assen V., Jönsson, Erik G., Kendler, Kenneth S., Kirov, George, Knight, Jo, Lencz, Todd, Levinson, Douglas F., Li, Qingqin S., Liu, Jianjun, Malhotra, Anil K., McCarroll, Steven A., McQuillin, Andrew, Moran, Jennifer L., Mortensen, Preben B., Mowry, Bryan J., Ophoff, Roel A., Owen, Michael J., Palotie, Aarno, Pato, Carlos N., Petryshen, Tracey L., Posthuma, Danielle, Riley, Brien P., Sham, Pak C., Sklar, Pamela, Clair, David S., Weinberger, Daniel R., Wendland, Jens R., Werge, Thomas, Daly, Mark J., O'Donovan, Michael C., Sullivan, Patrick F., Keller, Matthew C., Biological Psychology, Johnson, Emma C, Bjelland, Douglas W, Howrigan, Daniel P, Abdellaoui, Abdel, Lee, S Hong, Keller, Matthew C, and Schizophrenia Working Group of the Psychiatric Genomics Consortium
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0301 basic medicine ,Male ,Cancer Research ,Heredity ,Ecology, Evolution, Behavior and Systematics ,Molecular Biology ,Genetics ,Genetics (clinical) ,Social Sciences ,Genome-wide association study ,Disease ,030105 genetics & heredity ,Runs of Homozygosity ,Homozygosity ,Consanguinity ,Sociology ,Polymorphism (computer science) ,Consortia ,Medicine and Health Sciences ,Genetics(clinical) ,Inbreeding ,Ecology ,Depression ,Homozygote ,Genomics ,3. Good health ,Schizophrenia ,Research Design ,Physical Sciences ,Female ,Statistics (Mathematics) ,Research Article ,lcsh:QH426-470 ,Evolution ,Replication Studies ,inbreeding ,Single-nucleotide polymorphism ,Biology ,Genome Complexity ,Research and Analysis Methods ,Polymorphism, Single Nucleotide ,03 medical and health sciences ,SDG 17 - Partnerships for the Goals ,Behavior and Systematics ,SDG 3 - Good Health and Well-being ,Mental Health and Psychiatry ,medicine ,Confidence Intervals ,Humans ,replication study ,Mood Disorders ,Genome, Human ,Biology and Life Sciences ,Computational Biology ,medicine.disease ,schizophrenia ,lcsh:Genetics ,030104 developmental biology ,homozygosity ,Mathematics ,Genome-Wide Association Study - Abstract
It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest., Author Summary It is well known that mating between relatives increases the risk that a child will have a rare recessive genetic disease, but there has also been increasing interest and inconsistent findings on whether inbreeding is a risk factor for common, complex psychiatric disorders such as schizophrenia. The best powered study to date investigating this theory predicted that the odds of developing schizophrenia increase by approximately 17% for every additional percent of the genome that shows evidence of inbreeding. In this replication, we used genome-wide single nucleotide polymorphism data from 18,562 schizophrenia cases and 21,268 controls to quantify the degree to which they were inbred and to test the hypothesis that schizophrenia cases show higher mean levels of inbreeding. Contrary to the original study, we did not find evidence for distant inbreeding to play a role in schizophrenia risk. There are various confounding factors that could explain the discrepancy in results from the original study and our replication, and this should serve as a cautionary note–careful attention should be paid to issues like ascertainment when using the data from genome-wide case-control association studies for secondary analyses for which the data may not have originally been intended.
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- 2016
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4. Proof of concept: Molecular prediction of schizophrenia risk
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Docherty, Anna R., primary, Moscati, Arden, additional, Adkins, Daniel E., additional, Wallace, Gemma T., additional, Kumar, Guarav, additional, Riley, Brien P., additional, Corvin, Aiden, additional, Anthony O’Neill, F., additional, Gill, Michael, additional, Kendler, Kenneth S., additional, Sullivan, Patrick F., additional, Fanous, Ayman H., additional, and Bacanu, Silviu-Alin, additional
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- 2017
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5. Apoptotic Engulfment Pathway and Schizophrenia.
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Xiangning Chen, Cuie Sun, Qi Chen, Anthony O'Neill, F., Walsh, Dermot, Fanous, Ayman H., Chowdari, Kodavali V., Nimgaonkar, Vishwajit L., Scott, Adrian, Schwab, Sibylle G., Wildenauer, Dieter B., Ronglin Che, Wei Tang, Yongyong Shi, Lin He, Xiong-jian Luo, Bing Su, Edwards, Todd L., Zhongming Zhao, and Kendler, Kenneth S.
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APOPTOSIS ,SCHIZOPHRENIA ,GENES ,GENOTYPE-environment interaction ,CELL death ,CELLS - Abstract
Background: Apoptosis has been speculated to be involved in schizophrenia. In a previously study, we reported the association of the MEGF10 gene with the disease. In this study, we followed the apoptotic engulfment pathway involving the MEGF10, GULP1, ABCA1 and ABCA7 genes and tested their association with the disease. Methodology/Principal Findings: Ten, eleven and five SNPs were genotyped in the GULP1, ABCA1 and ABCA7 genes respectively for the ISHDSF and ICCSS samples. In all 3 genes, we observed nominally significant associations. Rs2004888 at GULP1 was significant in both ISHDSF and ICCSS samples (p = 0.0083 and 0.0437 respectively). We sought replication in independent samples for this marker and found highly significant association (p = 0.0003) in 3 Caucasian replication samples. But it was not significant in the 2 Chinese replication samples. In addition, we found a significant 2-marker (rs2242436 * rs3858075) interaction between the ABCA1 and ABCA7 genes in the ISHDSF sample (p = 0.0022) and a 3-marker interaction (rs246896 * rs4522565 * rs3858075) amongst the MEGF10, GULP1 and ABCA1 genes in the ICCSS sample (p = 0.0120). Rs3858075 in the ABCA1 gene was involved in both 2- and 3-marker interactions in the two samples. Conclusions/Significance: From these data, we concluded that the GULP1 gene and the apoptotic engulfment pathway are involved in schizophrenia in subjects of European ancestry and multiple genes in the pathway may interactively increase the risks to the disease. [ABSTRACT FROM AUTHOR]
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- 2009
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6. Dynamic changes of functional segregation and integration in vulnerability and resilience to schizophrenia.
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Duan J, Xia M, Womer FY, Chang M, Yin Z, Zhou Q, Zhu Y, Liu Z, Jiang X, Wei S, Anthony O'Neill F, He Y, Tang Y, and Wang F
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- Adolescent, Adult, Cerebral Cortex physiopathology, Female, Humans, Male, Middle Aged, Nerve Net physiopathology, Schizophrenia physiopathology, Young Adult, Cerebral Cortex diagnostic imaging, Magnetic Resonance Imaging methods, Nerve Net diagnostic imaging, Schizophrenia diagnostic imaging, Schizophrenic Psychology
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Schizophrenia (SZ) is a highly heritable disease with neurodevelopmental origins and significant functional brain network dysfunction. Functional network is heavily influenced by neurodevelopment processes and can be characterized by the degree of segregation and integration. This study examines functional segregation and integration in SZ and their first-degree relatives (high risk [HR]) to better understand the dynamic changes in vulnerability and resiliency, and disease markers. Resting-state functional magnetic resonance imaging data acquired from 137 SZ, 89 HR, and 210 healthy controls (HCs). Small-worldness σ was computed at voxel level to quantify balance between segregation and integration. Interregional functional associations were examined based on Euclidean distance between regions and reflect degree of segregation and integration. Distance strength maps were used to localize regions of altered distance-based functional connectivity. σ was significantly decreased in SZ compared to HC, with no differences in high risk (HR). In three-group comparison, significant differences were noted in short-range connectivity (primarily in the primary sensory, motor and their association cortices, and the thalamus) and medium/long-range connectivity (in the prefrontal cortices [PFCs]). Decreased short- and increased medium/long-range connectivity was found in SZ. Decreased short-range connectivity was seen in SZ and HR, while HR had decreased medium/long-range connectivity. We observed disrupted balance between segregation and integration in SZ, whereas relatively preserved in HR. Similarities and differences between SZ and HR, specific changes of SZ were found. These might reflect dynamic changes of segregation in primary cortices and integration in PFCs in vulnerability and resilience, and disease markers in SZ., (© 2019 Wiley Periodicals, Inc.)
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- 2019
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