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Your search keyword '"Amanda B Zheutlin"' showing total 19 results
Start Over Author "Amanda B Zheutlin" Topic 0302 clinical medicine
19 results on '"Amanda B Zheutlin"'

1. Physical activity offsets genetic risk for incident depression assessed via electronic health records in a biobank cohort study

Author

Murray B. Stein, Erin C. Dunn, Karmel W. Choi, Min-Jung Wang, Elizabeth W. Karlson, Amanda B Zheutlin, Rebecca A. Karlson, and Jordan W. Smoller

Subjects
Male, Multifactorial Inheritance, Poison control, Context (language use), Suicide prevention, Article, Occupational safety and health, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Databases, Genetic, Injury prevention, Electronic Health Records, Humans, Medicine, Exercise, Depression (differential diagnoses), Depressive Disorder, Major, Depression, business.industry, Middle Aged, 030227 psychiatry, Psychiatry and Mental health, Clinical Psychology, Cohort, Female, business, 030217 neurology & neurosurgery, Genome-Wide Association Study, Demography, Cohort study
Abstract

Background Physical activity is increasingly recognized as an important modifiable factor for depression. However, the extent to which individuals with stable risk factors for depression, such as high genetic vulnerability, can benefit from the protective effects of physical activity, remains unknown. Using a longitudinal biobank cohort integrating genomic data from 7,968 individuals of European ancestry with high-dimensional electronic health records and lifestyle survey responses, we examined whether physical activity was prospectively associated with reduced risk for incident depression in the context of genetic vulnerability. Methods We identified individuals with incident episodes of depression, based on two or more diagnostic billing codes for a depressive disorder within 2 years following their lifestyle survey, and no such codes in the year prior. Polygenic risk scores were derived based on large-scale genome-wide association results for major depression. We tested main effects of physical activity and polygenic risk scores on incident depression, and effects of physical activity within stratified groups of polygenic risk. Results Polygenic risk was associated with increased odds of incident depression, and physical activity showed a protective effect of similar but opposite magnitude, even after adjusting for BMI, employment status, educational attainment, and prior depression. Higher levels of physical activity were associated with reduced odds of incident depression across all levels of genetic vulnerability, even among individuals at highest polygenic risk. Conclusions Real-world data from a large healthcare system suggest that individuals with high genetic vulnerability are more likely to avoid incident episodes of depression if they are physically active.

Published
2019
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2. An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression

Author

Murray B. Stein, Karmel W. Choi, Kristen Nishimi, Jonathan R. I. Coleman, Tian Ge, Gerome Breen, Karestan C. Koenen, Amanda B Zheutlin, Jordan W. Smoller, Chia-Yen Chen, Andrew Ratanatharathorn, and Erin C. Dunn

Subjects
Adult, Male, Exposome, Multifactorial Inheritance, Depression/etiology, Genomic data, Preventive Psychiatry, Bioinformatics, Article, Screen Time, 03 medical and health sciences, Exercise/psychology, 0302 clinical medicine, Risk Factors, Mendelian randomization, Medicine, Humans, Sleep Hygiene, Multifactorial Inheritance/genetics, Exercise, Depression (differential diagnoses), business.industry, Depression, Mendelian Randomization Analysis, 030227 psychiatry, Diet, Psychiatry and Mental health, Databases as Topic, Polygenic risk score, Female, Epidemiologic Methods, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

OBJECTIVE: Efforts to prevent depression, the leading cause of disability worldwide, have focused on a limited number of candidate factors. Using phenotypic and genomic data from over 100,000 UK Biobank participants, the authors sought to systematically screen and validate a wide range of potential modifiable factors for depression.METHODS: Baseline data were extracted for 106 modifiable factors, including lifestyle (e.g., exercise, sleep, media, diet), social (e.g., support, engagement), and environmental (e.g., green space, pollution) variables. Incident depression was defined as minimal depressive symptoms at baseline and clinically significant depression at follow-up. At-risk individuals for incident depression were identified by polygenic risk scores or by reported traumatic life events. An exposure-wide association scan was conducted to identify factors associated with incident depression in the full sample and among at-risk individuals. Two-sample Mendelian randomization was then used to validate potentially causal relationships between identified factors and depression.RESULTS: Numerous factors across social, sleep, media, dietary, and exercise-related domains were prospectively associated with depression, even among at-risk individuals. However, only a subset of factors was supported by Mendelian randomization evidence, including confiding in others (odds ratio=0.76, 95% CI=0.67, 0.86), television watching time (odds ratio=1.09, 95% CI=1.05, 1.13), and daytime napping (odds ratio=1.34, 95% CI=1.17, 1.53).CONCLUSIONS: Using a two-stage approach, this study validates several actionable targets for preventing depression. It also demonstrates that not all factors associated with depression in observational research may translate into robust targets for prevention. A large-scale exposure-wide approach combined with genetically informed methods for causal inference may help prioritize strategies for multimodal prevention in psychiatry.

Published
2020
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3. SNP Variants at 16p13.11 Clarify the Role of the NDE1/miR-484 Locus in Major Mental Illness in Finland

Author

Alfredo Ortega-Alonso, Tyrone D. Cannon, Sebastian Therman, Tiina Paunio, Annamari Tuulio-Henriksson, Erkki Isometsä, Outi Linnaranta, Jaana Suvisaari, Liisa Ukkola-Vuoti, Jaakko Kaprio, William Hennah, Minna Torniainen-Holm, Jouko Lönnqvist, Vishal Sinha, Pekka Jylhä, Amanda B Zheutlin, Iiris Hovatta, Institute for Molecular Medicine Finland, Medicum, Department of Psychology and Logopedics, William Hennah / Principal Investigator, Behavioural Sciences, Centre of Excellence in Complex Disease Genetics, Department of Public Health, Mind and Matter, Iiris Hovatta / Principal Investigator, Genetics, SLEEPWELL Research Program, Department of Psychiatry, HUS Psychiatry, Clinicum, Neuroscience Center, and Biosciences

Subjects
0301 basic medicine, Genetics, 515 Psychology, education, Haplotype, Locus (genetics), Single-nucleotide polymorphism, Biology, Mental illness, medicine.disease, 3124 Neurology and psychiatry, 3142 Public health care science, environmental and occupational health, Copy Number Polymorphism, 03 medical and health sciences, Psychiatry and Mental health, 030104 developmental biology, 0302 clinical medicine, medicine, 1182 Biochemistry, cell and molecular biology, SNP, Gene, 030217 neurology & neurosurgery, Genotype determination
Abstract

Through copy number variations, the 16p13.11 locus has been consistently linked to mental disorders. This locus contains the NDE1 gene, which also encodes microRNA-484. Both of them have been highlighted to play a role in the etiology of mental illness. A 4-SNP haplotype spanning this locus has been shown to associate with schizophrenia in Finnish females. Here we set out to identify any functional variations implicated by this haplotype. We used a sequencing and genotyping study design to identify variations of interest in a Finnish familial cohort ascertained for schizophrenia. We identified 295 variants through sequencing, none of which were located directly within microRNA-484. Two variants were observed to associate with schizophrenia in a sex-dependent manner (females only) in the whole schizophrenia familial cohort (rs2242549 P = .00044; OR = 1.20, 95% CI 1.03–1.40; rs881803 P = .00021; OR = 1.20, 95% CI 1.02–1.40). Both variants were followed up in additional psychiatric cohorts, with neuropsychological traits, and gene expression data, in order to further examine their role. Gene expression data from the familial schizophrenia cohort demonstrated a significant association between rs881803 and 1504 probes (FDR q < 0.05). These were significantly enriched for genes that are predicted miR-484 targets (n = 54; P = .000193), and with probes differentially expressed between the sexes (n = 48; P = .000187). While both SNPs are eQTLs for NDE1, rs881803 is located in a predicted transcription factor binding site. Based on its location and association pattern, we conclude that rs881803 is the prime functional candidate under this locus, affecting the roles of both NDE1 and miR-484 in psychiatric disorders.

Published
2020
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4. Association between physical exercise and mental health in 1·2 million individuals in the USA between 2011 and 2015: a cross-sectional study

Author

Adam M Chekroud, Amanda B Zheutlin, Ralitza Gueorguieva, Martin P. Paulus, Harlan M. Krumholz, John H. Krystal, and Sammi R Chekroud

Subjects
Adult, Male, Gerontology, Adolescent, Cross-sectional study, Physical exercise, Disease, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Quality of life, Humans, Medicine, 030212 general & internal medicine, Young adult, Exercise, Biological Psychiatry, Depression (differential diagnoses), Aged, Aged, 80 and over, business.industry, Mental Disorders, Middle Aged, Mental health, United States, Psychiatry and Mental health, Cross-Sectional Studies, Mental Health, Socioeconomic Factors, Quality of Life, Regression Analysis, Marital status, Female, Self Report, business, 030217 neurology & neurosurgery
Abstract

Summary Background Exercise is known to be associated with reduced risk of all-cause mortality, cardiovascular disease, stroke, and diabetes, but its association with mental health remains unclear. We aimed to examine the association between exercise and mental health burden in a large sample, and to better understand the influence of exercise type, frequency, duration, and intensity. Methods In this cross-sectional study, we analysed data from 1 237 194 people aged 18 years or older in the USA from the 2011, 2013, and 2015 Centers for Disease Control and Prevention Behavioral Risk Factors Surveillance System survey. We compared the number of days of bad self-reported mental health between individuals who exercised and those who did not, using an exact non-parametric matching procedure to balance the two groups in terms of age, race, gender, marital status, income, education level, body-mass index category, self-reported physical health, and previous diagnosis of depression. We examined the effects of exercise type, duration, frequency, and intensity using regression methods adjusted for potential confounders, and did multiple sensitivity analyses. Findings Individuals who exercised had 1·49 (43·2%) fewer days of poor mental health in the past month than individuals who did not exercise but were otherwise matched for several physical and sociodemographic characteristics (W=7·42 × 1010, p Interpretation In a large US sample, physical exercise was significantly and meaningfully associated with self-reported mental health burden in the past month. More exercise was not always better. Differences as a function of exercise were large relative to other demographic variables such as education and income. Specific types, durations, and frequencies of exercise might be more effective clinical targets than others for reducing mental health burden, and merit interventional study. Funding Cloud computing resources were provided by Microsoft.

Published
2018
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5. Penetrance and pleiotropy of polygenic risk scores for schizophrenia in 106,160 patients across four health care systems

Author

Peter Straub, Christopher F. Chabris, Douglas M. Ruderfer, Laura M. Huckins, Jordan W. Smoller, Chia-Yen Chen, H. Lester Kirchner, Jessica Dennis, Lea K. Davis, Arden Moscati, Tian Ge, Richard Karlsson Linnér, Eli A. Stahl, Amanda B Zheutlin, Victor M. Castro, Alexander W. Charney, Nicole Restrepo, Economics, and Amsterdam Neuroscience - Complex Trait Genetics

Subjects
Male, Multifactorial Inheritance, Schizophrenia (object-oriented programming), Penetrance, Cognitive neuroscience, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Risk Factors, Intervention (counseling), Health care, mental disorders, Medicine, Humans, Genetic Predisposition to Disease, business.industry, Genetic Pleiotropy, Middle Aged, 030227 psychiatry, Psychiatry and Mental health, Pleiotropy (drugs), Risk stratification, Schizophrenia, Polygenic risk score, Female, business, Delivery of Health Care, 030217 neurology & neurosurgery, Clinical psychology
Abstract

Objective: Individuals at high risk for schizophrenia may benefit from early intervention, but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts. The authors sought to test the utility of this approach in clinical settings and to evaluate the broader health consequences of high genetic risk for schizophrenia. Methods: The authors used electronic health records for 106,160 patients from four health care systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from summary statistics and tested for association with 1,359 disease categories, including schizophrenia and psychosis, in phenome-wide association studies. Effects were combined through meta-analysis across sites. Results: PRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS, 1.55; 95% CI=1.4, 1.7), and patients in the highest risk decile of the PRS distribution had up to 4.6-fold higher odds of schizophrenia compared with those in the bottom decile (95% CI=2.9, 7.3). PRSs were also positively associated with other phenotypes, including anxiety, mood, substance use, neurological, and personality disorders, as well as suicidal behavior, memory loss, and urinary syndromes; they were inversely related to obesity. Conclusions: The study demonstrates that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in health care settings and has pleiotropic effects on related psychiatric disorders as well as other medical syndromes. The results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in health care systems.

Published
2019
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6. A two-stage approach to identifying and validating modifiable factors for the prevention of depression

Author

Andrew Ratanatharathorn, Erin C. Dunn, Karmel W. Choi, Murray B. Stein, Chia-Yen Chen, Jonathan R. I. Coleman, Tian Ge, Jordan W. Smoller, Karestan C. Koenen, Kristen Nishimi, Gerome Breen, and Amanda B Zheutlin

Subjects
Gerontology, 0303 health sciences, business.industry, Confounding, Social engagement, Mental health, Biobank, 3. Good health, Clinical trial, 03 medical and health sciences, 0302 clinical medicine, Multiple comparisons problem, Mendelian randomization, Medicine, 030212 general & internal medicine, business, Depression (differential diagnoses), 030304 developmental biology
Abstract

BackgroundAlthough depression is recognized as the leading cause of disability worldwide, decades of research have identified few actionable preventive factors. Using phenotypic and genomic data from the UK Biobank, we took advantage of a unique opportunity to screen a wide range of potentially modifiable factors that could offset known risk factors for depression.MethodsWe curated baseline data on more than 100 lifestyle and environmental factors in participants’ lives, including behavioral (e.g., exercise, sleep, media use, diet), social (e.g., support, activities), and environmental (e.g., greenspace, pollution) variables. In a follow-up survey, participants reported on their traumatic life experiences and mental health, including depression. Polygenic risk scores for depression were generated based on large-scale genome-wide association results. Excluding those meeting criteria for depression at baseline, we identified at-risk individuals at high predicted probability (> 90th percentile) for clinically significant depression at follow-up based on their (i) polygenic risk, or (ii) reported traumatic life events. Using a factors-wide design corrected for multiple testing and adjusted for potential confounders, we identified modifiable factors associated with follow-up depression in the full sample and among at-risk individuals. Using a two-sample Mendelian randomization (MR) design, we then examined which significant factors showed potential causal influences on depression risk, or vice versa.ResultsA range of baseline modifiable factors were prospectively associated with follow-up depression, including factors related to social engagement, physical activity, media use, and diet. MR follow-up analyses provided further support for the effects of social support-seeking, TV use, and other factors on depression risk.ConclusionAs the field increasingly quantifies the role of genetic factors in complex conditions such as depression, knowledge of modifiable factors that could offset one’s genetic risk has become highly relevant. Here, we present an approach to screening for potentially modifiable factors that may offset the risk of depression in general and among at-risk individuals. In light of the burden of disease associated with depression and the urgent need for actionable preventive strategies, this approach could help prioritize candidates for follow-up studies including clinical trials for depression prevention.

Published
2019
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7. Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders

Author

Phil Lee, Richard Anney, Pieter J. Hoekstra, Barbara Franke, Geschwind Dh, Michael C. Neale, Yen-Chen Anne Feng, Edwin H. Cook, Anttila, E Stahl, Borglum Ad, Kenneth S. Kendler, Santangelo Sl, Wray Nr, Danielle Posthuma, Carol A. Mathews, Sintia Iole Belangero, Amanda B Zheutlin, Cynthia M. Bulik, Jeremiah M. Scharf, Laramie E. Duncan, Luis Augusto Rohde, Jacob Rosenthal, Anna Keski-Rahkonen, Stein Mb, Fanous Ah, Zhaozhong Zhu, Karen S. Mitchell, J Kaprio, Breen G, Michel G. Nivard, G. Kirov, John I. Nurnberger, Patrick F. Sullivan, Daly Mj, Michael Conlon O'Donovan, Andreassen Oa, Hyejung Won, Wang Mm, Faraone Sv, Mattheisen M, Benjamin M. Neale, Gelernter J, Smoller Jw, Henry R. Kranzler, Thornton Lm, Clement C. Zai, Ripke S, Elliot M. Tucker-Drob, Howard J. Edenberg, Lewis Cm, McIntosh Am, Tobias Banaschewski, Dongmei Yu, Andrew D. Grotzinger, Walters Jt, Raymond K. Walters, Giovanni Coppola, and Jurjen J. Luykx

Subjects
0303 health sciences, medicine.medical_specialty, Biology, medicine.disease, Genome, Tourette syndrome, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Pleiotropy, Anorexia nervosa (differential diagnoses), Autism spectrum disorder, Schizophrenia, medicine, Bipolar disorder, Psychiatry, 030217 neurology & neurosurgery, Depression (differential diagnoses), 030304 developmental biology
Abstract

SummaryGenetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

Published
2019
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8. Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Author

Laura M. Thornton, Paul Lichtenstein, Verneri Anttila, Diego Albani, Josep Antoni Ramos-Quiroga, Roger A.H. Adan, Monika Schlögelhofer, Stephen Sanders, Enrique Castelao, Klaus Berger, Nina Dalkner, Urs Heilbronner, Engilbert Sigurdsson, Pablo Mir, Fuquan Zhang, James T.R. Walters, Patrick F. Sullivan, Fragiskos Gonidakis, F. Kyle Satterstrom, Sara Marsal, Per Hoffmann, Amy Perry, Valentina Ciullo, Beate Herpertz-Dahlmann, Catharina Lavebratt, Kieran C. Murphy, Tammy Hedderly, Hyun Ju Hong, Evald Saemundsen, Sascha B. Fischer, Hailiang Huang, Andrew D. Grotzinger, Nienke Vulink, Murray B. Stein, Mark A. Frye, Laura J. Scott, David Curtis, Todd Lencz, Janiece E. DeSocio, Richard A. Belliveau, Eduard Vieta, Andrea Dietrich, Wade H. Berrettini, Kenneth S. Kendler, Marquis P. Vawter, Paul S. Nestadt, Michael E. Talkowski, Manuel Mattheisen, Ingrid Agartz, Elisa Docampo, Bernhard T. Baune, Stefan Ehrlich, Jolanta Lissowska, Felecia Cerrato, Terje Nærland, Robin M. Murray, Jennifer Reichert, Annette M. Hartmann, Hannelore Ehrenreich, Howard J. Edenberg, Katherine A. Halmi, Qingqin S. Li, Peristera Paschou, Marie Bækvad-Hansen, Esther Walton, Alessio Maria Monteleone, Ted Reichborn-Kjennerud, Frank Bellivier, Jungeun Song, D. Blake Woodside, Young Shin Kim, Jochen Seitz, Jacques Pantel, Palmiero Monteleone, Erika L. Nurmi, Rodney J. Scott, Kang Sim, Ekaterina A. Khramtsova, Udo Dannlowski, Rolf Adolfsson, Danielle Posthuma, Melissa J. Green, Laura Ibanez-Gomez, Jakob Grove, Elvira Bramon, Gregory L. Hanna, Cynthia M. Bulik, Yiran Guo, Stephan Ripke, Mary M. Robertson, Harald N. Aschauer, Adebayo Anjorin, Joanna Martin, Bertram Müller-Myhsok, Deborah Kaminská, Jose Guzman-Parra, Benedetta Nacmias, Erik G. Jönsson, Jonathan R. I. Coleman, Douglas F. Levinson, Hamdi Mbarek, Gun Peggy Knudsen, Karin Egberts, Mette Nyegaard, Patrik K. E. Magnusson, Mark Adams, Douglas Blackwood, Elisabeth B. Binder, Marcus Ising, Anna R. Docherty, Jim van Os, Nese Direk, Lina Martinsson, Maria Arranz, Christel M. Middeldorp, Stefan Kloiber, Sintia Iole Belangero, Eske M. Derks, Ingrid Melle, Erlend Bøen, Jan Haavik, Federica Piras, Unna N. Danner, Anil K. Malhotra, Gerome Breen, Stephen V. Faraone, Amanda B Zheutlin, Timothy Poterba, Stephan Ruhrmann, Inge Joa, Ulrik Fredrik Malt, Sarah E. Bergen, Federica Tozzi, Lauren A. Weiss, Hana Papezova, Dominic Holland, Elliot S. Gershon, Jaakko Kaprio, Merete Nordentoft, Scott D. Gordon, Christopher Pittenger, Keun-Ah Cheon, Jennifer Jordan, Philip Gorwood, Myrna M. Weissman, Preben Bo Mortensen, Melissa A. Munn-Chernoff, Isobel Heyman, Eun-Young Shin, Christie L. Burton, Katherine Gordon-Smith, Sietske G. Helder, Peter Nagy, Till F. M. Andlauer, Yunpeng Wang, Young Key Kim, Kate Langley, Søren Dalsgaard, Richard Delorme, Torbjørn Elvsåshagen, Bennett L. Leventhal, Giovanni Gambaro, Christos Androutsos, Jennifer Tübing, Marion Roberts, Annelie Nordin Adolfsson, Hakon Hakonarson, Dorothy E. Grice, Vaughan J. Carr, Konstantinos Tziouvas, Stephanie Zerwas, Cathy L. Barr, Michael Conlon O'Donovan, Per Qvist, Beate St Pourcain, Samuel Kuperman, Leila Karhunen, Jack Samuels, Markus M. Nöthen, Martien J H Kas, Alfonso Tortorella, Mikael Landén, Jennifer Crosbie, Marco A. Grados, Joanna M. Biernacka, Paul D. Arnold, Irene A. Malaty, Jurjen J. Luykx, Nicholas Bass, Naomi R. Wray, Catharina A. Hartman, Christina M. Hultman, Michael S. Okun, Brandon Wormley, Michael Bauer, Daniel J. Smith, Ian Jones, Kathryn Roeder, Brien P. Riley, Caroline M. Nievergelt, Katrin Gade, Sarah Kittel-Schneider, Roy H. Perlis, James R. Mitchell, Ziarih Hawi, James Lee, Liz Forty, William E. Bunney, Thomas Damm Als, Catherine Schaefer, Digby Quested, Matteo Cassina, Anna C. Koller, Patrick Turley, Agnes A. Steixner, Anu Raevuori, Assen Jablensky, Peter Holmans, Dong-Ho Song, S. Evelyn Stewart, Jan K. Buitelaar, Fernando S. Goes, Alexander Münchau, Ayman H. Fanous, Nicolas Ramoz, James B. Potash, Monica Gratacos Mayora, Tobias Banaschewski, Céline S. Reinbold, Renata Rizzo, Arianna Di Florio, Lenka Foretova, Gianfranco Spalletta, Aarno Palotie, Eleftheria Zeggini, Lawrence W. Brown, Julie K. O'Toole, Lynn E. DeLisi, Ulrich Schall, Mary Roberson, Barbara J. Coffey, Bryan J. Mowry, Murray J. Cairns, Dan J. Stein, Glyn Lewis, Marta Ribasés, C. Robert Cloninger, Bettina Konte, John B. Vincent, Duncan S. Palmer, Radhika Kandaswamy, Christine Ladd-Acosta, Lars Alfredsson, Frank Visscher, Ulrike Schmidt, Aiden Corvin, Susan L. Santangelo, Brenda W.J.H. Penninx, David J. Porteous, Tetsuya Ando, Arne E. Vaaler, Bru Cormand, Laura Carlberg, Claire Churchhouse, Manfred Stuhrmann, Niamh Mullins, Christine Søholm Hansen, Cathy L. Budman, Hartmut Imgart, Dan E. Arking, James J. McGough, Michael Gill, Christel Depienne, Roland Burghardt, Antonio Julià, Anders M. Dale, Sven Sandin, Katharina Domschke, Maria Grigoroiu-Serbanescu, Susana Jiménez-Murcia, Marianne Giørtz Pedersen, Zsanett Tarnok, Gisli Baldursson, Michele T. Pato, David M. Hougaard, Thorgeir E. Thorgeirsson, Katharina Bey, Kerstin J. Plessen, Margaret A. Richter, Ole A. Andreassen, Claudine Laurent-Levinson, Leonid Padyukov, Jacques Mallet, Daniela Degortes, John R. Kelsoe, Robert D. Levitan, Andreas Reif, Chaim Huyser, Derek W. Morris, Sina Wanderer, William Byerley, Edna Grünblatt, E.J.C. de Geus, Hyejung Won, Josephine Elia, Rudolf Uher, Jay A. Tischfield, Andreas Karwautz, Gustavo Turecki, Pieter J. Hoekstra, Dorret I. Boomsma, Jacob Rosenthal, Daniele Cusi, Michael C. Neale, Sara Mostafavi, Gwyneth Zai, F. Anthony O'Neill, Gary Donohoe, Karola Rehnström, Harry Brandt, Helena Gaspar, Francis J. McMahon, H-Erich Wichmann, Andrew W. Bergen, Giovanni Coppola, Lea K. Davis, Lenka Slachtova, Olav B. Smeland, Erin C. Dunn, Nicholas G. Martin, Allan L. Naarden, Jo Knight, Cristina Sánchez-Mora, Masashi Ikeda, Lorraine Southam, Sandro Sorbi, Barbara Franke, Martin Schalling, Russell Schachar, Yen-Chen Anne Feng, Kirsten R. Müller-Vahl, André Scherag, Zhaozhong Zhu, Eric A. Storch, Páll Magnússon, David Cohen, Olafur O Gudmundsson, Harvey S. Singer, Brian Kelly, Jonas Bybjerg-Grauholm, Blanca Garcia-Delgar, Thomas Hansen, Carmel M. Loughland, Christine Lochner, Stacy Steinberg, Martin Woods, Jorge A. Quiroz, Raquel Rabionet, Alden Y. Huang, Janice M. Fullerton, María Soler Artigas, Hans J. Grabe, Philip Asherson, Margit Burmeister, Alicia R. Martin, Martin A. Kennedy, Janet Treasure, Anders D. Børglum, Eva C. Schulte, Andreas Hartmann, Frans Henskens, Youl-Ri Kim, Jens Treutlein, Joanna Hauser, Manfred M. Fichter, Damiaan Denys, Ann E. Pulver, Kelly L. Klump, Paul Sandor, Michael Wagner, Philippe Courtet, Sandra Van der Auwera, Susanne Lucae, Eystein Stordal, Michel G. Nivard, Maurizio Clementi, Astrid Morer, Philip B. Mitchell, Huda Akil, Edwin H. Cook, Jennifer L. Moran, Donald W. Black, Jeremiah M. Scharf, Jana Strohmaier, Colm McDonald, Meg M.-J. Wang, Richard M. Myers, Stephanie Godard, Pablo V. Gejman, Athanasios Maras, Marcella Rietschel, Nancy G. Buccola, Konstantinos Hatzikotoulas, Dalila Pinto, Jouke-Jan Hottenga, Kari Stefansson, James S. Sutcliffe, Andres Metspalu, Amaia Hervás, Joel Gelernter, Wolfgang Herzog, Paula Rovira, Gunnar Morken, Tara Murphy, Mark Weiser, Vincent Millischer, Frank Dudbridge, Dan Rujescu, Vladimir Bencko, Valdo Ricca, Kimberly Chambert, Guy A. Rouleau, James J. Crowley, Thomas G. Schulze, Toni-Kim Clarke, Triinu Peters, Gudrun Wagner, Daniel A. Geller, Henry R. Kranzler, G. Bragi Walters, Vera Golimbet, Clement C. Zai, Nigel Williams, Andreas Birgegård, Joseph D. Buxbaum, Elliot M. Tucker-Drob, Jerome C. Foo, Tracey L. Petryshen, Daniel P. Howrigan, Hunna J. Watson, Franziska Degenhardt, Peter R. Schofield, Jesper Buchhave Poulsen, Stefan Herms, Johannes Hebebrand, Mario Maj, George Kirov, Fabrizio Piras, Sara McDevitt, James T. McCracken, Carol A. Mathews, Michael John Owen, Peter Falkai, Donald L. Gilbert, Enda M. Byrne, Fernando Fernández-Aranda, Csaba Barta, Stéphane Jamain, Jubao Duan, Dongmei Yu, Danielle C. Cath, Ole Mors, Sigrun Hope, Laramie E. Duncan, Alan R. Sanders, Sang-Yun Oh, Carsten Bøcker Pedersen, Henning Tiemeier, Roseann E. Peterson, Raymond K. Walters, Margarita C T Slof-Op 't Landt, Madeline Alexander, Stephanie Le Hellard, Ina Giegling, Annemarie A. van Elburg, Steven P. Hamilton, Vesna Boraska Perica, Thomas V. Fernandez, Danielle M. Dick, Francesco Bettella, Roel A. Ophoff, Grant W. Montgomery, Gerald Nestadt, Nakao Iwata, Jessica H. Baker, Walter H. Kaye, Jeremy M. Silverman, Mark J. Daly, Robert A. King, Sarah E. Medland, Anastasios Konstantinidis, Robert D. Oades, Samuel H. Zinner, Steven Crawford, Daniel H. Geschwind, Patrick W. L. Leung, Martin Alda, Marie Navratilova, Pak C. Sham, Paul A. Tooney, Tian Ge, Veit Roessner, Martin Preisig, Thomas Werge, Eli A. Stahl, David A. Collier, Stephanie H. Witt, Dermot Walsh, Miquel Casas, Anna Keski-Rahkonen, Jane H. Christensen, Silvia De Rubeis, Giorgio Pistis, Sven Cichon, Bruno Etain, Dominique Campion, O. Joseph Bienvenu, Christian Dina, Manolis Kogevinas, Thomas Espeseth, Benjamin M. Neale, Ditte Demontis, Klaus-Peter Lesch, Marina Mitjans, Tiffany A. Greenwood, Marcos Madruga-Garrido, Sibylle G. Schwab, Oedegaard Ketil Joachim, Hreinn Stefansson, Sara A. Paciga, Monica Forzan, Dieter B. Wildenauer, Lena Backlund, A. Jeremy Willsey, Carlos N. Pato, Nicholas John Craddock, Inge A. Meijer, Sandra K. Loo, Filip Rybakowski, Tracey D. Wade, Scott J. Crow, Bernard Lerer, Valsamma Eapen, Esben Agerbo, Andrew M. McIntosh, Luis Augusto Rohde, Susan L. 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A., Schaefer, C., Schulte, E. C., Shi, J., Smith, D. J., Thomson, P. A., Tiemeier, H., Uher, R., van der Auwera, S., Weissman, M. M., Alexander, M., Begemann, M., Bramon, E., Buccola, N. G., Cairns, M. J., Campion, D., Carr, V. J., Cloninger, C. R., Cohen, D., Collier, D. A., Corvin, A., Delisi, L. E., Donohoe, G., Dudbridge, F., Duan, J., Freedman, R., Gejman, P. V., Golimbet, V., Godard, S., Ehrenreich, H., Hartmann, A. M., Henskens, F. A., Ikeda, M., Iwata, N., Jablensky, A. V., Joa, I., Jonsson, E. G., Kelly, B. J., Knight, J., Konte, B., Laurent-Levinson, C., Lee, J., Lencz, T., Lerer, B., Loughland, C. M., Malhotra, A. K., Mallet, J., Mcdonald, C., Mitjans, M., Mowry, B. J., Murphy, K. C., Murray, R. M., O'Neill, F. A., Oh, S. -Y., Palotie, A., Pantelis, C., Pulver, A. E., Petryshen, T. L., Quested, D. J., Riley, B., Sanders, A. R., Schall, U., Schwab, S. G., Scott, R. J., Sham, P. C., Silverman, J. M., Sim, K., Steixner, A. A., Tooney, P. A., van Os, J., Vawter, M. P., Walsh, D., Weiser, M., Wildenauer, D. B., Williams, N. M., Wormley, B. K., Zhang, F., Androutsos, C., Arnold, P. D., Barr, C. L., Barta, C., Bey, K., Bienvenu, O. J., Black, D. W., Brown, L. W., Budman, C., Cath, D., Cheon, K. -A., Ciullo, V., Coffey, B. J., Cusi, D., Davis, L. K., Denys, D., Depienne, C., Dietrich, A., Eapen, V., Falkai, P., Fernandez, T. V., Garcia-Delgar, B., Geller, D. A., Gilbert, D. L., Grados, M. A., Greenberg, E., Grunblatt, E., Hagstrom, J., Hanna, G. L., Hartmann, A., Hedderly, T., Heiman, G. A., Heyman, I., Hong, H. J., Huang, A., Huyser, C., Ibanez-Gomez, L., Khramtsova, E. A., Kim, Y. K., Kim, Y. -S., King, R. A., Koh, Y. -J., Konstantinidis, A., Kook, S., Kuperman, S., Leventhal, B. L., Lochner, C., Ludolph, A. G., Madruga-Garrido, M., Malaty, I., Maras, A., Mccracken, J. T., Meijer, I. A., Mir, P., Morer, A., Muller-Vahl, K. R., Munchau, A., Murphy, T. L., Naarden, A., Nagy, P., Nestadt, G., Nestadt, P. S., Nicolini, H., Nurmi, E. L., Okun, M. S., Paschou, P., Piras, F., Pittenger, C., Plessen, K. J., Richter, M. A., Rizzo, R., Robertson, M., Roessner, V., Ruhrmann, S., Samuels, J. F., Sandor, P., Schlogelhofer, M., Shin, E. -Y., Singer, H., Song, D. -H., Song, J., Spalletta, G., Stein, D. J., Stewart, S. E., Storch, E. A., Stranger, B., Stuhrmann, M., Tarnok, Z., Tischfield, J. A., Tubing, J., Visscher, F., Vulink, N., Wagner, M., Walitza, S., Wanderer, S., Woods, M., Worbe, Y., Zai, G., Zinner, S. H., Sullivan, P. F., Franke, B., Daly, M. J., Bulik, C. M., Mcintosh, A. M., O'Donovan, M. C., Zheutlin, A., Andreassen, O. A., Borglum, A. D., Breen, G., Edenberg, H. J., Fanous, A. H., Faraone, S. V., Gelernter, J., Mathews, C. A., Mattheisen, M., Mitchell, K. S., Neale, M. C., Nurnberger, J. I., Ripke, S., Santangelo, S. L., Scharf, J. M., Stein, M. B., Thornton, L. M., Walters, J. T. R., Wray, N. R., Geschwind, D. H., Neale, B. M., Kendler, K. S., and Smoller, J. W.

Subjects
Netherlands Twin Register (NTR), cross-disorder genetics, Medizin, Genome-wide association study, Tourette syndrome, functional genomics, gene expression, genetic architecture, genetic correlation, GWAS, neurodevelopment, pleiotropy, psychiatric disorders, Psychiatric genetics, 0302 clinical medicine, Pleiotropy, functional genomic, WIDE ASSOCIATION, cross-disorder genetic, 0303 health sciences, Mental Disorders, Genetic Pleiotropy, HUMAN BRAIN, INSIGHTS, Autism spectrum disorder, Schizophrenia, DISEASES, GENETIC CORRELATIONS, medicine.medical_specialty, Neurogenesis, Quantitative Trait Loci, BF, Biology, GENOTYPE IMPUTATION, Psychiatric geneticscross-disorder geneticspsychiatric disorderspleiotropyneurodevelopmentGWASgenetic correlationgene expressiongenetic architecturefunctional genomics, Article, General Biochemistry, Genetics and Molecular Biology, psychiatric disorder, 03 medical and health sciences, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, Bipolar disorder, TRANSCRIPTOME, Psychiatry, 030304 developmental biology, Gwas, Psychiatric Genetics, Cross-disorder Genetics, Functional Genomics, Gene Expression, Genetic Architecture, Genetic Correlation, Neurodevelopment, Psychiatric Disorders, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], IDENTIFICATION, MUTATIONS, medicine.disease, Genetic architecture, DEMETHYLASE, RC0321, 1182 Biochemistry, cell and molecular biology, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

Published
2019
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9. Cognitive endophenotypes inform genome-wide expression profiling in schizophrenia

Author

Christina M. Hultman, Desmond J. Smith, Amanda B Zheutlin, Sebastian Therman, Rebecca G. Fortgang, Tyrone D. Cannon, Rachael W. Viehman, Jaana Suvisaari, and Jacqueline Borg

Subjects
Adult, Male, Bipolar Disorder, Endophenotypes, Twins, Genomics, Genome-wide association study, Article, 03 medical and health sciences, Cognition, 0302 clinical medicine, Memory, Humans, Registries, Finland, Exome sequencing, Aged, Sweden, Genetics, California Verbal Learning Test, Gene Expression Profiling, Middle Aged, Microarray Analysis, 030227 psychiatry, Gene expression profiling, Neuropsychology and Physiological Psychology, Gene Expression Regulation, Endophenotype, Leukocytes, Mononuclear, Schizophrenia, RNA, Female, Schizophrenic Psychology, Verbal memory, Cognition Disorders, Psychology, Neuroscience, 030217 neurology & neurosurgery, Genome-Wide Association Study, Diagnosis of schizophrenia
Abstract

Schizophrenia Schizophrenia is a highly heritable, genetically complex, and heterogeneous psychiatric syndrome. Twin and family studies estimate 80–85% of variance in disease liability can be accounted for by genetic factors (Cannon, Kaprio, Lonnqvist, Huttunen, & Koskenvuo, 1998). Thus, substantial efforts have been dedicated towards uncovering genetic loci increasing risk for schizophrenia. Though many methodologies have been employed including genome-wide surveys of common genetic polymorphisms (Purcell et al., 2009; Ripke et al., 2013; Schizophrenia Working Group of the Psychiatric Genomics, 2014), exome sequencing investigating rare variants (Fromer et al., 2014; Purcell et al., 2014), gene expression analyses (Gardiner et al., 2013; Guillozet-Bongaarts et al., 2014; Gulsuner et al., 2013), and integration of multiple methods (Hertzberg, Katsel, Roussos, Haroutunian, & Domany, 2015; Luo et al., 2015; van Eijk et al., 2014), nearly all gene-finding efforts in schizophrenia to date have employed diagnostic level classification as the phenotype of interest. However, there is substantial evidence that risk-increasing genes confer risk via impacting intermediate levels of impairment, such as cognitive dysfunction, suggesting that these may also be useful phenotypic targets in gene discovery studies (Cannon & Keller, 2006; Greenwood, Light, Swerdlow, Radant, & Braff, 2012; Lencz et al., 2014; Tan, Callicott, & Weinberger, 2008; Toulopoulou et al., 2007). Compared to the diagnosis of schizophrenia, which could imply dysfunction across a host of brain systems and signaling pathways, a given endophenotype provides a more constrained framework within which to interpret the functional-biological relevance of statistically identified genes (Heck et al., 2014; Ibrahim-Verbaas et al., 2015; Lencz et al., 2014). One of the most reliable endophenotypes in schizophrenia – and most profound areas of cognitive impairment – is verbal memory (Cannon et al., 2000; Greenwood et al., 2013; Schaefer, Giangrande, Weinberger, & Dickinson, 2013; van Erp et al., 2008). The California Verbal Learning Test (CVLT), a list-learning exercise, is a robust measure of memory impairment in schizophrenia (Haut, in prep; Stone et al., 2011; van Erp et al., 2008), is heritable (Carmelli, Swan, DeCarli, & Reed, 2002; Greenwood et al., 2007; Kremen et al., 2014; Panizzon et al., 2011), and shows intermediate levels of affection among relatives of patients with schizophrenia in twin and family studies (Greenwood et al., 2013; van Erp et al., 2008), supporting its role as a candidate endophenotype in genetic studies. Initial molecular genetic investigations of endophenotypes for schizophrenia have provided evidence that genes associated with putative cognitive endophenotypes at least partially overlap with those associated with schizophrenia (Heck et al., 2014; Lencz et al., 2014). However, so far this approach has been used largely to demonstrate the broad, shared genetic etiology between these phenotypes, rather than to identify specific genetic loci impinging on both, which is critical for elucidating the functional-physiologic significance of the underlying genetic associations. Furthermore, all of these studies have assayed common polymorphisms. Over 90% of common polymorphisms previously related to psychiatric illness are located in regulatory regions of DNA, rather than in coding regions where mutations more directly affect protein structure, suggesting that many of these loci may exert their effects via regulation of gene expression (Kim et al., 2014; Maurano et al., 2012). Thus, examining gene expression in relation to a cognitive endophenotype for schizophrenia may yield insights into genotypic effects on disease status and help to elucidate mechanisms by which cognitive dysfunction manifests in this disease. In the current study, we used a discordant twin design to identify genes differentially expressed in relation to verbal memory performance, a cognitive endophenotype for schizophrenia. Gene expression was assayed from peripheral blood mononuclear cells (PBMCs) – the most feasible way to assess expression levels in living patients. Gene expression in PBMCs is broadly heritable and correlates with central nervous system expression patterns (Cheung et al., 2003). While it is likely that some genes influencing memory performance will not be schizophrenia-related, given the endophenotypic pattern of the CVLT, which suggests shared genetic etiology between memory and schizophrenia, we expected some proportion of these memory-related genes to show differential expression by diagnostic status (Glahn et al., 2007; Greenwood et al., 2007; van Erp et al., 2008). This subset would represent a selection of genes potentially involved in those systems underlying memory impairment in schizophrenia. A twin design further allowed us to test the heritability of expression for each of these genes, dissociating potentially etiologically relevant genetic alterations from disease-related secondary effects.

Published
2016
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10. Penetrance and pleiotropy of polygenic risk scores for schizophrenia in 106,160 patients across four healthcare systems

Author

Amanda B Zheutlin, Jessica Dennis, Richard Karlsson Linnér, Arden Moscati, Nicole Restrepo, Peter Straub, Douglas Ruderfer, Victor M Castro, Chia-Yen Chen, Tian Ge, Laura M Huckins, Alexander Charney, H Lester Kirchner, Eli A Stahl, Christopher F Chabris, Lea K Davis, and Jordan W Smoller

Subjects
0303 health sciences, medicine.medical_specialty, business.industry, Disease, Odds ratio, medicine.disease, Penetrance, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Schizophrenia, mental disorders, medicine, Genetic Pleiotropy, Bipolar disorder, Diagnosis code, Psychiatry, business, 030217 neurology & neurosurgery, 030304 developmental biology, Diagnosis of schizophrenia
Abstract

OBJECTIVEIndividuals at high risk for schizophrenia may benefit from early intervention but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts, but its utility in clinical settings remains largely unexplored. Moreover, the broad health consequences of a high genetic risk of schizophrenia are poorly understood, despite being relevant to treatment decisions.METHODWe used electronic health records for 106,160 patients from four healthcare systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from summary statistics and tested for association with 1359 disease categories, including schizophrenia and psychosis, in phenome-wide association studies. Effects were combined through meta-analysis across sites.RESULTSPRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS=1.55 [95% confidence interval (CI), 1.4-1.7], p=4.48 x 10-16) and patients in the highest risk decile of the PRS distribution had up to 4.6-fold increased odds of schizophrenia compared to those in the bottom decile (95% CI, 2.9-7.3, p=1.37 x 10-10). PRSs were also positively associated with a range of other phenotypes, including anxiety, mood, substance use, neurological, and personality disorders, as well as suicidal behavior, memory loss, and urinary syndromes; they were inversely related to obesity.CONCLUSIONSWe demonstrate that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in healthcare settings and has pleiotropic effects on related psychiatric disorders as well as other medical syndromes. Our results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in healthcare systems.

Published
2018
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11. Predicting Barriers to Treatment for Depression in a U.S. National Sample: A Cross-Sectional, Proof-of-Concept Study

Author

Martin P. Paulus, David Foster, Amanda B Zheutlin, Girish Subramanyan, Ralitza Gueorguieva, Danielle M. Gerhard, Adam M Chekroud, Nikolaos Koutsouleris, Brita Roy, John H. Krystal, Abhishek Chandra, and Michelle Degli Esposti

Subjects
Adult, Male, Self-Assessment, Sample (statistics), Proof of Concept Study, Health Services Accessibility, Sampling Studies, Article, Treatment Refusal, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Healthcare delivery, Surveys and Questionnaires, Humans, 030212 general & internal medicine, Depression (differential diagnoses), Aged, Aged, 80 and over, Depressive Disorder, Primary Health Care, Middle Aged, Patient Acceptance of Health Care, United States, 030227 psychiatry, Psychotherapy, Psychiatry and Mental health, Cross-Sectional Studies, Logistic Models, Proof of concept, Female, Psychology, Clinical psychology
Abstract

Objective: Even though safe and effective treatments for depression are available, many individuals with a diagnosis of depression do not obtain treatment. This study aimed to develop a tool to identify persons who might not initiate treatment among those who acknowledge a need.Methods: Data were aggregated from the 2008–2014 U.S. National Survey on Drug Use and Health (N=391,753), including 20,785 adults given a diagnosis of depression by a health care provider in the 12 months before the survey. Machine learning was applied to self-report survey items to develop strategies for identifying individuals who might not get needed treatment.Results: A derivation cohort aggregated between 2008 and 2013 was used to develop a model that identified the 30.6% of individuals with depression who reported needing but not getting treatment. When applied to independent responses from the 2014 cohort, the model identified 72% of those who did not initiate treatment (pConclusions: Considerable work is needed to improve follow-up and retention rates after the critical initial meeting in which a patient is given a diagnosis of depression. Routinely collected information about patients with depression could identify those at risk of not obtaining needed treatment, which may inform the development and implementation of interventions to reduce the prevalence of untreated depression.

Published
2018

12. Polygenic Risk Scores: What Are They Good For?

Author

Amanda B Zheutlin and David A. Ross

Subjects
Multifactorial Inheritance, MEDLINE, Genome-wide association study, Computational biology, Risk Assessment, Article, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Medicine, Humans, Genetic Predisposition to Disease, Gene–environment interaction, Biological Psychiatry, business.industry, Extramural, Depression, 030227 psychiatry, Schizophrenia, Polygenic risk score, Gene-Environment Interaction, Risk assessment, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Published
2018

13. Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia

Author

Nelson B. Freimer, Fred W. Sabb, Joel Gelernter, Christina M. Hultman, Edythe D. London, Robert M. Bilder, Adam M Chekroud, Renato Polimanti, Tyrone D. Cannon, and Amanda B Zheutlin

Subjects
0301 basic medicine, Adult, Male, Multivariate statistics, Multifactorial Inheritance, Genotype, Endophenotypes, Feature selection, Computational biology, Biology, Polymorphism, Single Nucleotide, Machine Learning, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Visual memory, Linear regression, Humans, Cognitive Dysfunction, Registries, Sweden, Cognition, Middle Aged, Twin study, United States, Random forest, Psychiatry and Mental health, 030104 developmental biology, Phenotype, Endophenotype, Schizophrenia, Female, 030217 neurology & neurosurgery, Regular Articles
Abstract

Genetic risk variants for schizophrenia have been linked to many related clinical and biological phenotypes with the hopes of delineating how individual variation across thousands of variants corresponds to the clinical and etiologic heterogeneity within schizophrenia. This has primarily been done using risk score profiling, which aggregates effects across all variants into a single predictor. While effective, this method lacks flexibility in certain domains: risk scores cannot capture nonlinear effects and do not employ any variable selection. We used random forest, an algorithm with this flexibility designed to maximize predictive power, to predict 6 cognitive endophenotypes in a combined sample of psychiatric patients and controls (N = 739) using 77 genetic variants strongly associated with schizophrenia. Tenfold cross-validation was applied to the discovery sample and models were externally validated in an independent sample of similar ancestry (N = 336). Linear approaches, including linear regression and task-specific polygenic risk scores, were employed for comparison. Random forest models for processing speed (P = .019) and visual memory (P = .036) and risk scores developed for verbal (P = .042) and working memory (P = .037) successfully generalized to an independent sample with similar predictive strength and error. As such, we suggest that both methods may be useful for mapping a limited set of predetermined, disease-associated SNPs to related phenotypes. Incorporating random forest and other more flexible algorithms into genotype-phenotype mapping inquiries could contribute to parsing heterogeneity within schizophrenia; such algorithms can perform as well as standard methods and can capture a more comprehensive set of potential relationships.

Published
2018

14. The Role of microRNA Expression in Cortical Development During Conversion to Psychosis

Author

Elaine F. Walker, Amanda B Zheutlin, Clark D. Jeffries, Daniel H. Mathalon, Jean Addington, Yoonho Chung, Adam M Chekroud, Tyrone D. Cannon, Carrie E. Bearden, Barbara A. Cornblatt, Scott W. Woods, Thomas H. McGlashan, Diana O. Perkins, Ming T. Tsuang, Kristin S. Cadenhead, and Larry J. Seidman

Subjects
0301 basic medicine, Male, Medical and Health Sciences, Cohort Studies, 0302 clinical medicine, Leukocytes, 2.1 Biological and endogenous factors, Developmental, Aetiology, Regulation of gene expression, Cerebral Cortex, Psychiatry, Microglia, Gene Expression Regulation, Developmental, Psychiatry and Mental health, medicine.anatomical_structure, Mental Health, Cerebral cortex, Cytokines, Original Article, Female, Algorithms, Biotechnology, Adult, Psychosis, Adolescent, Prodromal Symptoms, Biology, Proinflammatory cytokine, 03 medical and health sciences, Young Adult, Immune system, Predictive Value of Tests, Clinical Research, microRNA, medicine, Humans, Pharmacology, Psychology and Cognitive Sciences, Neurosciences, medicine.disease, Brain Disorders, MicroRNAs, 030104 developmental biology, Psychotic Disorders, Gene Expression Regulation, Synaptic plasticity, Schizophrenia, Neuroscience, 030217 neurology & neurosurgery
Abstract

In a recent report of the North American Prodrome Longitudinal Study (NAPLS), clinical high-risk individuals who converted to psychosis showed a steeper rate of cortical gray matter reduction compared with non-converters and healthy controls, and the rate of cortical thinning was correlated with levels of proinflammatory cytokines at baseline. These findings suggest a critical role for microglia, the resident macrophages in the brain, in perturbations of cortical maturation processes associated with onset of psychosis. Elucidating gene expression pathways promoting microglial action prior to disease onset would inform potential preventative intervention targets. Here we used a forward stepwise regression algorithm to build a classifier of baseline microRNA expression in peripheral leukocytes associated with annualized rate of cortical thinning in a subsample of the NAPLS cohort (N=74). Our cortical thinning classifier included nine microRNAs, p=3.63 × 10-08, R2=0.358, permutation-based p=0.039, the gene targets of which were enriched for intracellular signaling pathways that are important to coordinating inflammatory responses within immune cells (p

Published
2017

15. Complement Gene Expression Correlates with Superior Frontal Cortical Thickness in Humans

Author

Dana M Allswede, Martin Ingvar, Amanda B Zheutlin, Christina M. Hultman, Tyrone D. Cannon, Yoonho Chung, and Kevin M. Anderson

Subjects
0301 basic medicine, Adult, Male, Synaptic pruning, Gene Expression, Biology, behavioral disciplines and activities, 03 medical and health sciences, 0302 clinical medicine, Cortex (anatomy), Gene expression, medicine, Humans, RNA, Messenger, Gene, Aged, Pharmacology, Innate immune system, Microarray analysis techniques, Complement C5, Organ Size, Middle Aged, medicine.disease, Microarray Analysis, Magnetic Resonance Imaging, Complement system, Frontal Lobe, Psychiatry and Mental health, 030104 developmental biology, medicine.anatomical_structure, Schizophrenia, Original Article, Female, Neuroscience, Complement C1 Inhibitor Protein, 030217 neurology & neurosurgery
Abstract

Recent work suggests that genes encoding complement proteins that are active in the innate immune system may confer risk for schizophrenia by disrupting typical synaptic pruning in late adolescence. Alterations in the complement pathway may contribute to aberrant cortical thinning in schizophrenia prodromes and reduced prefrontal cortical thickness in chronic schizophrenia patients; however, this theory needs to be translated to humans. We conducted a series of analyses in a sample of adult Swedish twins enriched for schizophrenia (N=129) to assess the plausibility of a relationship between complement gene expression and cortical thickness that could go awry in the etiology of schizophrenia. First, we identified that peripheral mRNA expression levels of two complement genes (C5, SERPING1) made unique contributions to the variance in superior frontal cortical thickness among all participants. Vertex-wise maps of the association between gene expression levels and thickness across the cortex suggested that this relationship was especially strong with SERPING1 in the superior frontal region, consistent with the pattern of disruption in cortical thickness observed in schizophrenia. Additional analyses identified that these genes are expressed in the human superior frontal cortex, that heritable genetic factors influence SERPING1 gene expression levels, and that these associations are observed regardless of case status. These findings provide initial evidence linking the complement system with cortical thinning in humans, a process potentially involved in the pathogenesis of schizophrenia.

Published
2017

16. SU4. Complement Gene Expression Correlates With Superior Frontal Cortical Thickness in Humans

Author

Dana M Allswede, Amanda B Zheutlin, Tyrone D. Cannon, Christina M. Hultman, Kevin M. Anderson, Martin Ingvar, and Yoonho Chung

Subjects
03 medical and health sciences, Psychiatry and Mental health, Abstracts, 0302 clinical medicine, Gene expression, Biology, Neuroscience, 030217 neurology & neurosurgery, 030227 psychiatry, Complement (complexity)
Abstract

Background: Genes involved in the complement pathway of the innate immune system have been implicated in risk for schizophrenia. Emerging evidence suggests that this pathway is involved in synaptic pruning, a phenomenon that likely influences cortical thinning and may underlie reduction of cortical thickness in prefrontal regions in schizophrenia. However, a link between complement genes and cortical thickness has not yet been established in humans.

Published
2017

17. Neuregulin signaling pathway in smoking behavior

Author

Miina Ollikainen, Veikko Salomaa, Pamela A. F. Madden, Amanda B Zheutlin, Markus Perola, Sebastian Therman, Tyrone D. Cannon, Anu Loukola, Lili Milani, Samuli Ripatti, Tero Hiekkalinna, Richa Gupta, Liang He, Jaakko Kaprio, Beenish Qaiser, Tellervo Korhonen, School of Medicine / Public Health, Institute for Molecular Medicine Finland, University of Helsinki, Quantitative Genetics, Clinicum, Department of Public Health, Samuli Olli Ripatti / Principal Investigator, Biostatistics Helsinki, HUS Abdominal Center, Complex Disease Genetics, Epigenetics of Complex Diseases and Traits, and Genetic Epidemiology

Subjects
0301 basic medicine, Male, Nicotine, Receptor, ErbB-4, Genetic Linkage, Neuregulin-1, education, Addiction, Quantitative trait locus, Polymorphism, Single Nucleotide, 3124 Neurology and psychiatry, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Genetic linkage, medicine, Twins, Dizygotic, Genetics, Humans, Biological Psychiatry, ERBB4, Finland, Aged, Neuregulins, Neuregulin Receptor, business.industry, Smoking, Tobacco Use Disorder, Twins, Monozygotic, Middle Aged, medicine.disease, 3. Good health, Substance Withdrawal Syndrome, Psychiatry and Mental health, 030104 developmental biology, Nicotine withdrawal, Phenotype, Expression quantitative trait loci, Schizophrenia, Neuregulin, Original Article, Female, business, 030217 neurology & neurosurgery, medicine.drug, Signal Transduction
Abstract

Understanding molecular processes that link comorbid traits such as addictions and mental disorders can provide novel therapeutic targets. Neuregulin signaling pathway (NSP) has previously been implicated in schizophrenia, a neurodevelopmental disorder with high comorbidity to smoking. Using a Finnish twin family sample, we have previously detected association between nicotine dependence and ERBB4 (a neuregulin receptor), and linkage for smoking initiation at the ERBB4 locus on 2q33. Further, Neuregulin3 has recently been shown to associate with nicotine withdrawal in a behavioral mouse model. In this study, we scrutinized association and linkage between 15 036 common, low frequency and rare genetic variants in 10 NSP genes and phenotypes encompassing smoking and alcohol use. Using the Finnish twin family sample (N=1998 from 740 families), we detected 66 variants (representing 23 LD blocks) significantly associated (false discovery rate P, published version, peerReviewed

Published
2017

18. The NDE1 genomic locus can affect treatment of psychiatric illness through gene expression changes related to MicroRNA-484

Author

Liisa Ukkola-Vuoti, Minna Torniainen-Holm, Jaana Suvisaari, Maiju Pankakoski, Amanda B Zheutlin, Jari Haukka, Tiina Paunio, Alfredo Ortega-Alonso, Tyrone D. Cannon, Vishal Sinha, William Hennah, Jouko Lönnqvist, Nicholas J. Bradshaw, Sebastian Therman, Institute for Molecular Medicine Finland, Medicum, William Hennah / Principal Investigator, Clinicum, Department of Psychiatry, Jari Haukka / Principal Investigator, Department of Public Health, HUS Psychiatry, and Developmental Psychology Research Group

Subjects
0301 basic medicine, Male, 3124 Neurology and psychiatry, Exon, 0302 clinical medicine, PDE4B, Genotype, Gene expression, Pharmacology (medical), Copy-number variation, lcsh:QH301-705.5, COPY NUMBER VARIANTS, Genetics, 0303 health sciences, DISCI network, General Neuroscience, ASSOCIATION, miR-484, 3. Good health, Psychiatry and Mental health, Neurology, Female, SCHIZOPHRENIA SUSCEPTIBILITY, NDE1, Microtubule-Associated Proteins, Research Article, Antipsychotic Agents, BRAIN-DEVELOPMENT, Mental illness, schizophrenia, DISC1, microRNAs, genetics, Immunology, HAPLOTYPE, Nerve Tissue Proteins, Locus (genetics), Biology, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, DISC1 network, RISK-FACTOR, Cell Line, Tumor, CYTOCHROME-P450 2D6, Humans, SNP, NEURODEVELOPMENTAL DISORDERS, Gene, Biological Psychiatry, 030304 developmental biology, Pharmacology, MUTATIONS, gene expression, pharmacogenetics, Research, Haplotype, 3112 Neurosciences, 030227 psychiatry, Cytochrome P-450 CYP2C19, MicroRNAs, 030104 developmental biology, lcsh:Biology (General), Pharmacogenetics, biology.protein, 1182 Biochemistry, cell and molecular biology, Neurology (clinical), 030217 neurology & neurosurgery
Abstract

Genetic studies of familial schizophrenia in Finland have observed significant associations with a group of biologically related genes, DISC1 , NDE1 , NDEL1 , PDE4B and PDE4D , the ‘DISC1 network’. Here, we use gene expression and psychoactive medication use data to study their biological consequences and potential treatment implications. Gene expression levels were determined in 64 individuals from 18 families, while prescription medication information has been collected over a 10-year period for 931 affected individuals. We demonstrate that the NDE1 SNP rs2242549 associates with significant changes in gene expression for 2908 probes (2542 genes), of which 794 probes (719 genes) were replicable. A significant number of the genes altered were predicted targets of microRNA-484 ( p = 3.0 × 10 −8 ), located on a non-coding exon of NDE1 . Variants within the NDE1 locus also displayed significant genotype by gender interaction to early cessation of psychoactive medications metabolized by CYP2C19. Furthermore, we demonstrate that miR-484 can affect the expression of CYP2C19 in a cell culture system. Thus, variation at the NDE1 locus may alter risk of mental illness, in part through modification of miR-484, and such modification alters treatment response to specific psychoactive medications, leading to the potential for use of this locus in targeting treatment.

Published
2016
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19. Interaction of childhood urbanicity and variation in dopamine genes alters adult prefrontal function as measured by functional magnetic resonance imaging (fMRI)

Author

Amanda B Zheutlin, Justin Sturm, Daniel R. Weinberger, Raffaella Romano, Jesse Hochheiser, Barbara E. Spencer, Gianluca Ursini, Enrico D'Ambrosio, Alessandro Bertolino, Karen F. Berman, Joseph H. Callicott, Giuseppe Blasi, Ann Reifman, Stefano Marenco, and Jessica Reed

Subjects
Male, European People, Urban Population, Dopamine, lcsh:Medicine, Biochemistry, Brain mapping, Diagnostic Radiology, Urban Environments, Catecholamines, Cognition, Learning and Memory, Mathematical and Statistical Techniques, 0302 clinical medicine, Functional Magnetic Resonance Imaging, 11. Sustainability, Medicine and Health Sciences, Ethnicities, Amines, Child, lcsh:Science, Intelligence Tests, Brain Mapping, Multidisciplinary, medicine.diagnostic_test, Organic Compounds, Radiology and Imaging, Brain, Neurochemistry, Neurotransmitters, Environmental exposure, Magnetic Resonance Imaging, Terrestrial Environments, Italian People, Chemistry, Memory, Short-Term, Phenotype, Italy, Schizophrenia, Physical Sciences, Female, Anatomy, Statistics (Mathematics), Research Article, medicine.drug, Adult, Biogenic Amines, Genotype, Imaging Techniques, Cognitive Neuroscience, Prefrontal Cortex, Neuroimaging, Biology, Research and Analysis Methods, Catechol O-Methyltransferase, 03 medical and health sciences, Dopamine receptor D1, Diagnostic Medicine, Memory, Dopamine receptor D2, Mental Health and Psychiatry, medicine, Humans, Working Memory, Statistical Methods, Social Behavior, Receptors, Dopamine D2, Working memory, Receptors, Dopamine D1, Organic Chemistry, Ecology and Environmental Sciences, lcsh:R, Chemical Compounds, Biology and Life Sciences, medicine.disease, Hormones, United States, 030227 psychiatry, Social Class, People and Places, Cognitive Science, Population Groupings, Gene-Environment Interaction, lcsh:Q, Functional magnetic resonance imaging, Neuroscience, Mathematics, 030217 neurology & neurosurgery, Meta-Analysis
Abstract

Brain phenotypes showing environmental influence may help clarify unexplained associations between urban exposure and psychiatric risk. Heritable prefrontal fMRI activation during working memory (WM) is such a phenotype. We hypothesized that urban upbringing (childhood urbanicity) would alter this phenotype and interact with dopamine genes that regulate prefrontal function during WM. Further, dopamine has been hypothesized to mediate urban-associated factors like social stress. WM-related prefrontal function was tested for main effects of urbanicity, main effects of three dopamine genes-catechol-O-methyltransferase (COMT), dopamine receptor D1 (DRD1), and dopamine receptor D2 (DRD2)-and, importantly, dopamine gene-by-urbanicity interactions. For COMT, three independent human samples were recruited (total n = 487). We also studied 253 subjects genotyped for DRD1 and DRD2. 3T fMRI activation during the N-back WM task was the dependent variable, while childhood urbanicity, dopamine genotype, and urbanicity-dopamine interactions were independent variables. Main effects of dopamine genes and of urbanicity were found. Individuals raised in an urban environment showed altered prefrontal activation relative to those raised in rural or town settings. For each gene, dopamine genotype-by-urbanicity interactions were shown in prefrontal cortex-COMT replicated twice in two independent samples. An urban childhood upbringing altered prefrontal function and interacted with each gene to alter genotype-phenotype relationships. Gene-environment interactions between multiple dopamine genes and urban upbringing suggest that neural effects of developmental environmental exposure could mediate, at least partially, increased risk for psychiatric illness in urban environments via dopamine genes expressed into adulthood.

Published
2018
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