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1. Simulation model of power generation and the shadow effect of foldable solar panels used in agrivoltaics system

Author

Ramesh Kumar Lama and Heon Jeong

Subjects
agrivolatics systems, foldable panels, solar power, shadow effect, sustainable agriculture, General Works
Abstract

This paper presents a comprehensive analysis of foldable solar panels used in agrivoltaics systems (AVS), focusing on the dual benefits of optimized land use for agriculture and solar power generation. Employing simulation techniques, the study investigates the impact of inter-panel shadow effects on power generation in systems using multiple foldable solar panels. Key findings indicate that foldable panels achieve optimal performance during periods with shorter daylight hours, demonstrating high seasonal variability in power generation. The study shows that foldable panels, which can adjust their angle relative to the sun’s position, are particularly effective at reducing the loss of solar irradiance due to shading, compared to fixed panels. Additionally, this study highlights the potential of foldable solar panel systems in AVS to adapt to varying solar conditions, thereby enhancing land use optimization for sustainable agricultural and power generation practices.

Published
2024
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2. Simulation and real-life implementation of UAV autonomous landing system based on object recognition and tracking for safe landing in uncertain environments

Author

Ranjai Baidya and Heon Jeong

Subjects
autonomous landing, deep sort, distance transform, intelligent autonomous system, obstacle avoidance, object detection, Mechanical engineering and machinery, TJ1-1570, Electronic computers. Computer science, QA75.5-76.95
Abstract

The use of autonomous Unmanned Aerial Vehicles (UAVs) has been increasing, and the autonomy of these systems and their capabilities in dealing with uncertainties is crucial. Autonomous landing is pivotal for the success of an autonomous mission of UAVs. This paper presents an autonomous landing system for quadrotor UAVs with the ability to perform smooth landing even in undesirable conditions like obstruction by obstacles in and around the designated landing area and inability to identify or the absence of a visual marker establishing the designated landing area. We have integrated algorithms like version 5 of You Only Look Once (YOLOv5), DeepSORT, Euclidean distance transform, and Proportional-Integral-Derivative (PID) controller to strengthen the robustness of the overall system. While the YOLOv5 model is trained to identify the visual marker of the landing area and some common obstacles like people, cars, and trees, the DeepSORT algorithm keeps track of the identified objects. Similarly, using the detection of the identified objects and Euclidean distance transform, an open space without any obstacles to land could be identified if necessary. Finally, the PID controller generates appropriate movement values for the UAV using the visual cues of the target landing area and the obstacles. To warrant the validity of the overall system without risking the safety of the involved people, initial tests are performed, and a software-based simulation is performed before executing the tests in real life. A full-blown hardware system with an autonomous landing system is then built and tested in real life. The designed system is tested in various scenarios to verify the effectiveness of the system. The code is available at this repository: https://github.com/rnjbdya/Vision-based-UAV-autonomous-landing.

Published
2024
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3. An Efficient One-Dimensional Texture Representation Approach for Lung Disease Diagnosis

Author

Abrar Alabdulwahab, Hyun-Cheol Park, Heon Jeong, and Sang-Woong Lee

Subjects
deep learning, feed-forward network, image processing, feature extraction, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

The remarkable increase in published medical imaging datasets for chest X-rays has significantly improved the performance of deep learning techniques to classify lung diseases efficiently. However, large datasets require special arrangements to make them suitable, accessible, and practically usable in remote clinics and emergency rooms. Additionally, it increases the computational time and image-processing complexity. This study investigates the efficiency of converting the 2D chest X-ray into one-dimensional texture representation data using descriptive statistics and local binary patterns, enabling the use of feed-forward neural networks to efficiently classify lung diseases within a short time and with cost effectiveness. This method bridges diagnostic gaps in healthcare services and improves patient outcomes in remote hospitals and emergency rooms. It also could reinforce the crucial role of technology in advancing healthcare. Utilizing the Guangzhou and PA datasets, our one-dimensional texture representation achieved 99% accuracy with a training time of 10.85 s and 0.19 s for testing. In the PA dataset, it achieved 96% accuracy with a training time of 38.14 s and a testing time of 0.17 s, outperforming EfficientNet, EfficientNet-V2-Small, and MobileNet-V3-Small. Therefore, this study suggests that the dimensional texture representation is fast and effective for lung disease classification.

Published
2024
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4. Design and Performance Analysis of Foldable Solar Panel for Agrivoltaics System

Author

Ramesh Kumar Lama and Heon Jeong

Subjects
agrivoltaics system, foldable solar panel, renewable energy, solar tracking, sustainable agriculture, Chemical technology, TP1-1185
Abstract

This study investigates the use of a foldable solar panel system equipped with a dynamic tracking algorithm for agrivoltaics system (AVS) applications. It aims to simultaneously meet the requirements for renewable energy and sustainable agriculture. The design focuses on improving solar energy capture while facilitating crop growth through adjustable shading. The results show that foldable panels, controlled by the tracking algorithm, significantly outperform fixed panels in energy efficiency, achieving up to a 15% gain in power generation and uniform power generation throughout the day. Despite the presence of shadows of adjacent panels in the early morning and late evening, the system’s effectiveness in creating microclimates for diverse crops demonstrates its substantial value. The foldable design not only protects crops from adverse climate conditions across different seasons but also generates energy efficiently. This demonstrates a step forward in sustainable land use and food security.

Published
2024
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5. Anomaly Detection in Time Series Data Using Reversible Instance Normalized Anomaly Transformer

Author

Ranjai Baidya and Heon Jeong

Subjects
time series data, anomaly detection, attention mechanism, transformer, normalization, Chemical technology, TP1-1185
Abstract

Anomalies are infrequent in nature, but detecting these anomalies could be crucial for the proper functioning of any system. The rarity of anomalies could be a challenge for their detection as detection models are required to depend on the relations of the datapoints with their adjacent datapoints. In this work, we use the rarity of anomalies to detect them. For this, we introduce the reversible instance normalized anomaly transformer (RINAT). Rooted in the foundational principles of the anomaly transformer, RINAT incorporates both prior and series associations for each time point. The prior association uses a learnable Gaussian kernel to ensure a thorough understanding of the adjacent concentration inductive bias. In contrast, the series association method uses self-attention techniques to specifically focus on the original raw data. Furthermore, because anomalies are rare in nature, we utilize normalized data to identify series associations and employ non-normalized data to uncover prior associations. This approach enhances the modelled series associations and, consequently, improves the association discrepancies.

Published
2023
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6. SecAODV: A Secure Healthcare Routing Scheme Based on Hybrid Cryptography in Wireless Body Sensor Networks

Author

Heon Jeong, Sang-Woong Lee, Mazhar Hussain Malik, Efat Yousefpoor, Mohammad Sadegh Yousefpoor, Omed Hassan Ahmed, Mehdi Hosseinzadeh, and Amir Mosavi

Subjects
wireless body sensor networks (WBSNs), Internet of things (IoT), secure routing, security, healthcare, Medicine (General), R5-920
Abstract

In recent decades, the use of sensors has dramatically grown to monitor human body activities and maintain the health status. In this application, routing and secure data transmission are very important to prevent the unauthorized access by attackers to health data. In this article, we propose a secure routing scheme called SecAODV for heterogeneous wireless body sensor networks. SecAODV has three phases: bootstrapping, routing between cluster head nodes, and communication security. In the bootstrapping phase, the base station loads system parameters and encryption functions in the memory of sensor nodes. In the routing phase, each cluster head node calculates its degree based on several parameters, including, distance, residual energy, link quality, and the number of hops, to decide for rebroadcasting the route request (RREQ) message. In the communication security phase, a symmetric cryptography method is used to protect intra-cluster communications. Also, an asymmetric cryptography method is used to secure communication links between cluster head nodes. The proposed secure routing scheme is simulated in the network simulator version 2 (NS2) simulator. The simulation results are compared with the secure multi tier energy-efficient routing scheme (SMEER) and the centralized low-energy adaptive clustering hierarchy (LEACH-C). The results show that SecAODV improves end-to-end delay, throughput, energy consumption, packet delivery rate (PDR), and packet loss rate (PLR).

Published
2022
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7. Highly sensitive and multiplexed one-step RT-qPCR for profiling genes involved in the circadian rhythm using microparticles

Author

Mi Yeon Kim, Seungwon Jung, Junsun Kim, Heon Jeong Lee, Seunghwa Jeong, Sang Jun Sim, and Sang Kyung Kim

Subjects
Medicine, Science
Abstract

Abstract Given the growing interest in molecular diagnosis, highly extensive and selective detection of genetic targets from a very limited amount of samples is in high demand. We demonstrated the highly sensitive and multiplexed one-step RT-qPCR platform for RNA analysis using microparticles as individual reactors. Those particles are equipped with a controlled release system of thermo-responsive materials, and are able to capture RNA targets inside. The particle-based assay can successfully quantify multiple target RNAs from only 200 pg of total RNA. The assay can also quantify target RNAs from a single cell with the aid of a pre-concentration process. We carried out 8-plex one-step RT-qPCR using tens of microparticles, which allowed extensive mRNA profiling. The circadian cycles were shown by the multiplex one-step RT-qPCR in human cell and human hair follicles. Reliable 24-plex one-step RT-qPCR was developed using a single operation in a PCR chip without any loss of performance (i.e., selectivity and sensitivity), even from a single hair. Many other disease-related transcripts can be monitored using this versatile platform. It can also be used non–invasively for samples obtained in clinics.

Published
2021
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8. Predicting the Output of Solar Photovoltaic Panels in the Absence of Weather Data Using Only the Power Output of the Neighbouring Sites

Author

Heon Jeong

Subjects
solar photo voltaic, times series forecasting, meteorology, recurrent neural network, gated recurrent unit, long-short term memory, Chemical technology, TP1-1185
Abstract

There is an increasing need for capable models in the forecast of the output of solar photovoltaic panels. These models are vital for optimizing the performance and maintenance of PV systems. There is also a shortage of studies on forecasts of the output power of solar photovoltaics sites in the absence of meteorological data. Unlike common methods, this study explores numerous machine learning algorithms for forecasting the output of solar photovoltaic panels in the absence of weather data such as temperature, humidity and wind speed, which are often used when forecasting the output of solar PV panels. The considered models include Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN) and Transformer. These models were used with the data collected from 50 different solar photo voltaic sites in South Korea, which consist of readings of the output of each of the sites collected at regular intervals. This study focuses on obtaining multistep forecasts for the multi-in multi-out, multi-in uni-out and uni-in uni-out settings. Detailed experimentation was carried out in each of these settings. Finally, for each of these settings and different lookback and forecast lengths, the best models were also identified.

Published
2023
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9. YOLOv5 with ConvMixer Prediction Heads for Precise Object Detection in Drone Imagery

Author

Ranjai Baidya and Heon Jeong

Subjects
object detection, YOLOv5, ConvMixer, UAV imagery, Chemical technology, TP1-1185
Abstract

The potency of object detection techniques using Unmanned Aerial Vehicles (UAVs) is unprecedented due to their mobility. This potency has stimulated the use of UAVs with object detection functionality in numerous crucial real-life applications. Additionally, more efficient and accurate object detection techniques are being researched and developed for usage in UAV applications. However, object detection in UAVs presents challenges that are not common to general object detection. First, as UAVs fly at varying altitudes, the objects imaged via UAVs vary vastly in size, making the task at hand more challenging. Second due to the motion of the UAVs, there could be a presence of blur in the captured images. To deal with these challenges, we present a You Only Look Once v5 (YOLOv5)-like architecture with ConvMixers in its prediction heads and an additional prediction head to deal with minutely-small objects. The proposed architecture has been trained and tested on the VisDrone 2021 dataset, and the acquired results are comparable with the existing state-of-the-art methods.

Published
2022
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10. Study on the Integral Compensator Using Supercapacitor for Energy Harvesting in Low-Power Sections of Solar Energy

Author

So-Hyeon Jo, Joo Woo, Gi-Sig Byun, Jae-Hoon Jeong, and Heon Jeong

Subjects
solar energy, harvesting, supercapacitor, PV, Technology
Abstract

The risk of environmental pollution is a consequence of every kind of energy, including fossil fuels, nuclear power plants, and thermoelectric power plants. For the purpose of reducing the use ratio of such energy, research on eco-friendly energy is being actively carried out, and has shown that among all kinds of energy, solar energy has an advantage: it can supply us with inexhaustible clean energy. However, since solar energy depends on sunlight, the output may be unstable as it is influenced by weather or surrounding structures. In this paper, there is presented a control system which transmits power to a storage device, in a specific state, after the energy of the low-illumination section is charged in a supercapacitor using the accumulation-type controller by use of a supercapacitor. Feedback from the power output of photovoltaic panels (PVs) demonstrates that the power of the low-illumination section can be charged without being discarded. The charging rate was compared with other solar controllers being sold on the market, and the comparison was made through state of charge (SOC) measurements after the battery had been charged by photovoltaic panels for a whole day. It was confirmed that the solar controller, by use of supercapacitor integrator proposed in this paper, stored higher levels of energy than the existing solar controllers over the same hours and under the same conditions.

Published
2021
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13. Image-Based Gimbal Control in a Drone for Centering Photovoltaic Modules in a Thermal Image

Author

Hyun-Cheol Park, Sang-Woong Lee, and Heon Jeong

Subjects
drone, gimbal, thermal image, photovoltaic module, image processing, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

Recently, there have been many types of research applying drones with a thermal camera to detect deteriorations in photovoltaic (PV) modules. A thermal camera can measure temperatures on the surface of PV modules and find the deteriorated area. However, a thermal camera generally has a lower resolution than a visible camera because of the limitations of cost. Due to different resolutions between the visible and thermal cameras, there are often invalid frames from a thermal camera. In this paper, we describe a gimbal controller with a real-time image processing algorithm to control the angle of the camera to position the region of interest (ROI) in the center of target PV modules to solve this problem. We derived the horizontal angle and vertical position of ROI in visible images using image processing algorithms such as the Hough transform. These values are converted into a PID control signal for controlling the gimbal. This process makes the thermal camera capture the effective area of target PV modules. Finally, experimental results showed that the photovoltaic module’s control area was properly located at the center of the thermal image.

Published
2020
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14. Deterioration Diagnosis of Solar Module Using Thermal and Visible Image Processing

Author

Heon Jeong, Goo-Rak Kwon, and Sang-Woong Lee

Subjects
thermal image, photovoltaic module, hot spot, image processing, deterioration, Technology
Abstract

Several factors cause the output degradation of the photovoltaic (PV) module. The main affecting elements are the higher PV module temperature, the shaded cell, the shortened or conducting bypass diodes, and the soiled and degraded PV array. In this paper, we introduce an image processing technique that automatically identifies the module generating the hot spots in the solar module. In order to extract feature points, we used the maximally stable extremal regions (MSER) method, which derives the area of interest by using the inrange function, using the blue color of the PV module. We propose an effective matching method for feature points and a homography translation technique. The temperature data derivation method and the normal/ abnormal decision method are described in order to enhance the performance. The effectiveness of the proposed system was evaluated through experiments. Finally, a thermal image analysis of approximately 240 modules was confirmed to be 97% consistent with the visual evaluation in the experimental results.

Published
2020
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15. Automatic Detection System of Deteriorated PV Modules Using Drone with Thermal Camera

Author

Chris Henry, Sahadev Poudel, Sang-Woong Lee, and Heon Jeong

Subjects
photovoltaic power station, fault detection, autonomous drone, thermal image analysis, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

In the last few decades, photovoltaic (PV) power station installations have surged across the globe. The output efficiency of these stations deteriorates with the passage of time due to multiple factors such as hotspots, shaded cell or module, short-circuited bypass diodes, etc. Traditionally, technicians inspect each solar panel in a PV power station using infrared thermography to ensure consistent output efficiency. With the advancement of drone technology, researchers have proposed to use drones equipped with thermal cameras for PV power station monitoring. However, most of these drone-based approaches require technicians to manually control the drone which in itself is a cumbersome task in the case of large PV power stations. To tackle this issue, this study presents an autonomous drone-based solution. The drone is mounted with both RGB (Red, Green, Blue) and thermal cameras. The proposed system can automatically detect and estimate the exact location of faulty PV modules among hundreds or thousands of PV modules in the power station. In addition, we propose an automatic drone flight path planning algorithm which eliminates the requirement of manual drone control. The system also utilizes an image processing algorithm to process RGB and thermal images for fault detection. The system was evaluated on a 1-MW solar power plant located in Suncheon, South Korea. The experimental results demonstrate the effectiveness of our solution.

Published
2020
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17. Telepsychiatry in the Treatment of Major Depressive Disorders

Author

Cho, Chul-Hyun, Lee, Heon-Jeong, Kim, Yong-Ku, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, Rosenhouse-Dantsker, Avia, Series Editor, Gerlai, Robert, Series Editor, and Kim, Yong-Ku, editor

Published
2024
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18. Extended Kalman Filter-Based State of Charge and State of Power Estimation Algorithm for Unmanned Aerial Vehicle Li-Po Battery Packs

Author

Sunghun Jung and Heon Jeong

Subjects
equivalent circuit models (ECM), extended Kalman filter (EKF), state of charge (SOC), state of power (SOP), Technology
Abstract

Customer requirements for unmanned aerial vehicles (UAVs) with long flight times are increasing exponentially in the personal, commercial, and military use areas. Due to their limited payload, large numbers of on-board battery packs cannot be used and this is the main reason behind the need for battery management software (BMS) packages with state of charge (SOC) estimation functions to increase the flight time. At the same time, as the UAV application range has extended widely, the size of UAVs has increased and heavy-duty UAVs are slowly appearing. As a result, the system operating power of the UAVs has been increased tremendously and their safe system power operation has become an issue. This is the main reason for the need of BMS having state of power (SOP) estimation functions. In this work a 6 S Li-Po battery pack is simulated with two ladder equivalent circuit models (ECMs) considering an impedance effect whose parameters are found using hybrid pulse power characterization (HPPC) current patterns with parameter determination using the table-based linear interpolation (TBLI) method. Two state estimation methods, including the current integration method and the extended Kalman filter (EKF) method are developed and the estimation accuracies of SOC and SOP are compared. Results show that the most accurate SOC estimation turns out to be 0.1477% (indoor test with HPPC), 0.1324% (outdoor test with 0 kg payload), and 0.2021% (outdoor test with 10 kg payload). Also, the most accurate SOP estimation error turns out to be 1.2% (indoor test with HPPC), 3.6% (outdoor test with 0 kg payload), and 4.2% (outdoor test with 10 kg payload).

Published
2017
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20. Genome-wide association study and polygenic risk score analysis for schizophrenia in a Korean population

Author

Lee, Dongbin, Baek, Ji Hyun, Kim, Yujin, Lee, Byung Dae, Cho, Eun-Young, Joo, Eun-Jeong, Ahn, Yong Min, Kim, Se Hyun, Chung, Young-Chul, Rami, Fatima Zahra, Kim, Se Joo, Kim, Sung-Wan, Myung, Woojae, Ha, Tae Hyon, Lee, Heon-Jeong, Oh, Hayoung, Lee, Kyu Young, Kim, Min Ji, Kang, Chae Yeong, Jeon, Sumoa, Jo, Anna, Yu, Hyeona, Jeong, Seunghwa, Ha, Kyooseob, Kim, Beomsu, Shim, Injeong, Cho, Chamlee, Huang, Hailiang, Won, Hong-Hee, and Hong, Kyung Sue

Published
2024
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22. Neurobiological and behavioral mechanisms of circadian rhythm disruption in bipolar disorder: A critical multi‐disciplinary literature review and agenda for future research from the ISBD task force on chronobiology

Author

McCarthy, Michael J, Gottlieb, John F, Gonzalez, Robert, McClung, Colleen A, Alloy, Lauren B, Cain, Sean, Dulcis, Davide, Etain, Bruno, Frey, Benicio N, Garbazza, Corrado, Ketchesin, Kyle D, Landgraf, Dominic, Lee, Heon‐Jeong, Marie‐Claire, Cynthia, Nusslock, Robin, Porcu, Alessandra, Porter, Richard, Ritter, Philipp, Scott, Jan, Smith, Daniel, Swartz, Holly A, and Murray, Greg

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Behavioral and Social Science, Sleep Research, Prevention, Neurosciences, Brain Disorders, Clinical Research, Mental Health, Serious Mental Illness, Bipolar Disorder, Mental health, Animals, Behavioral Research, Chronobiology Disorders, Circadian Rhythm, Humans, Sleep, actigraphy, animal models, biomarker, chronobiology, circadian, clock gene, levels of analysis, light, lithium, sleep, Psychiatry, Clinical sciences, Health services and systems
Abstract

AimSymptoms of bipolar disorder (BD) include changes in mood, activity, energy, sleep, and appetite. Since many of these processes are regulated by circadian function, circadian rhythm disturbance has been examined as a biological feature underlying BD. The International Society for Bipolar Disorders Chronobiology Task Force (CTF) was commissioned to review evidence for neurobiological and behavioral mechanisms pertinent to BD.MethodDrawing upon expertise in animal models, biomarkers, physiology, and behavior, CTF analyzed the relevant cross-disciplinary literature to precisely frame the discussion around circadian rhythm disruption in BD, highlight key findings, and for the first time integrate findings across levels of analysis to develop an internally consistent, coherent theoretical framework.ResultsEvidence from multiple sources implicates the circadian system in mood regulation, with corresponding associations with BD diagnoses and mood-related traits reported across genetic, cellular, physiological, and behavioral domains. However, circadian disruption does not appear to be specific to BD and is present across a variety of high-risk, prodromal, and syndromic psychiatric disorders. Substantial variability and ambiguity among the definitions, concepts and assumptions underlying the research have limited replication and the emergence of consensus findings.ConclusionsFuture research in circadian rhythms and its role in BD is warranted. Well-powered studies that carefully define associations between BD-related and chronobiologically-related constructs, and integrate across levels of analysis will be most illuminating.

Published
2022

26. Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia

Author

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., Jr., 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, Kimberley D., Chan, Raymond C.K., Chan, Ronald Y.L., Chen, Eric Y.H., Cheng, Wei, Cheung, Eric FC., Chong, Siow Ann, Cloninger, C. Robert, Cohen, David, Cohen, Nadine, Cormican, Paul, Craddock, Nick, Crowley, James J., Curtis, David, Davidson, Michael, Davis, Kenneth L., Degenhardt, Franziska, 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., Frank, Josef, Franke, Lude, Freedman, Robert, Freimer, Nelson B., Friedl, Marion, Friedman, Joseph I., Fromer, Menachem, Genovese, Giulio, 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., Herms, Stefan, 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, Keller, Matthew C., 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, Lee, Jimmy, Lee, S. Hong, 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., Maier, Wolfgang, Mallet, Jacques, Marsal, Sara, Mattheisen, Manuel, 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, Nenadic, Igor, Nertney, Deborah A., Nestadt, Gerald, Nicodemus, Kristin K., Nikitina-Zake, Liene, Nisenbaum, Laura, Nordin, Annelie, O'Callaghan, Eadbhard, O'Dushlaine, Colm, O'Neill, F. Anthony, 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, Ruderfer, Douglas M., Salomaa, Veikko, Sanders, Alan R., Schall, Ulrich, Schubert, Christian R., Schulze, Thomas G., 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, Strohmaier, Jana, Stroup, T Scott, 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, Witt, Stephanie H., 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., Cichon, Sven, 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., Nöthen, Markus M., Ophoff, Roel A., Owen, Michael J., Palotie, Aarno, Pato, Carlos N., Petryshen, Tracey L., Posthuma, Danielle, Rietschel, Marcella, Riley, Brien P., Rujescu, Dan, Sham, Pak C., Sklar, Pamela, St Clair, David, Weinberger, Daniel R., Wendland, Jens R., Werge, Thomas, Daly, Mark J., Sullivan, Patrick F., O'Donovan, Michael C., Qin, Shengying, Sawa, Akira, Kahn, Rene, Hong, Kyung Sue, Shi, Wenzhao, Tsuang, Ming, Itokawa, Masanari, Feng, Gang, Glatt, Stephen J., Ma, Xiancang, Tang, Jinsong, Ruan, Yunfeng, Liu, Ruize, Zhu, Feng, Horiuchi, Yasue, Lee, Byung Dae, Joo, Eun-Jeong, Myung, Woojae, Ha, Kyooseob, Won, Hong-Hee, Baek, Ji Hyung, Chung, Young Chul, Kim, Sung-Wan, Kusumawardhani, Agung, Chen, Wei J., Hwu, Hai-Gwo, Hishimoto, Akitoyo, Otsuka, Ikuo, Sora, Ichiro, Toyota, Tomoko, Yoshikawa, Takeo, Kunugi, Hiroshi, Hattori, Kotaro, Ishiwata, Sayuri, Numata, Shusuke, Ohmori, Tetsuro, Arai, Makoto, Ozeki, Yuji, Fujii, Kumiko, Kim, Se Joo, Lee, Heon-Jeong, Ahn, Yong Min, Kim, Se Hyun, Akiyama, Kazufumi, Shimoda, Kazutaka, Kinoshita, Makoto, Hsu, Yu-Han H., Pintacuda, Greta, Nacu, Eugeniu, Kim, April, Tsafou, Kalliopi, Petrossian, Natalie, Crotty, William, Suh, Jung Min, Riseman, Jackson, Martin, Jacqueline M., Biagini, Julia C., Mena, Daya, Ching, Joshua K.T., Malolepsza, Edyta, Li, Taibo, Singh, Tarjinder, Ge, Tian, Egri, Shawn B., Tanenbaum, Benjamin, Stanclift, Caroline R., Apffel, Annie M., Carr, Steven A., Schenone, Monica, Jaffe, Jake, Fornelos, Nadine, Eggan, Kevin C., and Lage, Kasper

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

Author

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

Published
2022
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30. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author

Mullins, Niamh, Forstner, Andreas J., O’Connell, Kevin S., Coombes, Brandon, Coleman, Jonathan R. I., Qiao, Zhen, Als, Thomas D., Bigdeli, Tim B., Børte, Sigrid, Bryois, Julien, Charney, Alexander W., Drange, Ole Kristian, Gandal, Michael J., Hagenaars, Saskia P., Ikeda, Masashi, Kamitaki, Nolan, Kim, Minsoo, Krebs, Kristi, Panagiotaropoulou, Georgia, Schilder, Brian M., Sloofman, Laura G., Steinberg, Stacy, Trubetskoy, Vassily, Winsvold, Bendik S., Won, Hong-Hee, Abramova, Liliya, Adorjan, Kristina, Agerbo, Esben, Al Eissa, Mariam, Albani, Diego, Alliey-Rodriguez, Ney, Anjorin, Adebayo, Antilla, Verneri, Antoniou, Anastasia, Awasthi, Swapnil, Baek, Ji Hyun, Bækvad-Hansen, Marie, Bass, Nicholas, Bauer, Michael, Beins, Eva C., Bergen, Sarah E., Birner, Armin, Bøcker Pedersen, Carsten, Bøen, Erlend, Boks, Marco P., Bosch, Rosa, Brum, Murielle, Brumpton, Ben M., Brunkhorst-Kanaan, Nathalie, Budde, Monika, Bybjerg-Grauholm, Jonas, Byerley, William, Cairns, Murray, Casas, Miquel, Cervantes, Pablo, Clarke, Toni-Kim, Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Cunningham, Julie, Curtis, David, Czerski, Piotr M., Dale, Anders M., Dalkner, Nina, David, Friederike S., Degenhardt, Franziska, Djurovic, Srdjan, Dobbyn, Amanda L., Douzenis, Athanassios, Elvsåshagen, Torbjørn, Escott-Price, Valentina, Ferrier, I. Nicol, Fiorentino, Alessia, Foroud, Tatiana M., Forty, Liz, Frank, Josef, Frei, Oleksandr, Freimer, Nelson B., Frisén, Louise, Gade, Katrin, Garnham, Julie, Gelernter, Joel, Giørtz Pedersen, Marianne, Gizer, Ian R., Gordon, Scott D., Gordon-Smith, Katherine, Greenwood, Tiffany A., Grove, Jakob, Guzman-Parra, José, Ha, Kyooseob, Haraldsson, Magnus, Hautzinger, Martin, Heilbronner, Urs, Hellgren, Dennis, Herms, Stefan, Hoffmann, Per, Holmans, Peter A., Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S., Kalman, Janos L., Kamatani, Yoichiro, Kennedy, James L., Kittel-Schneider, Sarah, Knowles, James A., Kogevinas, Manolis, Koromina, Maria, Kranz, Thorsten M., Kranzler, Henry R., Kubo, Michiaki, Kupka, Ralph, Kushner, Steven A., Lavebratt, Catharina, Lawrence, Jacob, Leber, Markus, Lee, Heon-Jeong, Lee, Phil H., Levy, Shawn E., Lewis, Catrin, Liao, Calwing, Lucae, Susanne, Lundberg, Martin, MacIntyre, Donald J., Magnusson, Sigurdur H., Maier, Wolfgang, Maihofer, Adam, Malaspina, Dolores, Maratou, Eirini, Martinsson, Lina, Mattheisen, Manuel, McCarroll, Steven A., McGregor, Nathaniel W., McGuffin, Peter, McKay, James D., Medeiros, Helena, Medland, Sarah E., Millischer, Vincent, Montgomery, Grant W., Moran, Jennifer L., Morris, Derek W., Mühleisen, Thomas W., O’Brien, Niamh, O’Donovan, Claire, Olde Loohuis, Loes M., Oruc, Lilijana, Papiol, Sergi, Pardiñas, Antonio F., Perry, Amy, Pfennig, Andrea, Porichi, Evgenia, Potash, James B., Quested, Digby, Raj, Towfique, Rapaport, Mark H., DePaulo, J. Raymond, Regeer, Eline J., Rice, John P., Rivas, Fabio, Rivera, Margarita, Roth, Julian, Roussos, Panos, Ruderfer, Douglas M., Sánchez-Mora, Cristina, Schulte, Eva C., Senner, Fanny, Sharp, Sally, Shilling, Paul D., Sigurdsson, Engilbert, Sirignano, Lea, Slaney, Claire, Smeland, Olav B., Smith, Daniel J., Sobell, Janet L., Søholm Hansen, Christine, Soler Artigas, Maria, Spijker, Anne T., Stein, Dan J., Strauss, John S., Świątkowska, Beata, Terao, Chikashi, Thorgeirsson, Thorgeir E., Toma, Claudio, Tooney, Paul, Tsermpini, Evangelia-Eirini, Vawter, Marquis P., Vedder, Helmut, Walters, James T. R., Witt, Stephanie H., Xi, Simon, Xu, Wei, Yang, Jessica Mei Kay, Young, Allan H., Young, Hannah, Zandi, Peter P., Zhou, Hang, Zillich, Lea, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Alfredsson, Lars, Babadjanova, Gulja, Backlund, Lena, Baune, Bernhard T., Bellivier, Frank, Bengesser, Susanne, Berrettini, Wade H., Blackwood, Douglas H. R., Boehnke, Michael, Børglum, Anders D., Breen, Gerome, Carr, Vaughan J., Catts, Stanley, Corvin, Aiden, Craddock, Nicholas, Dannlowski, Udo, Dikeos, Dimitris, Esko, Tõnu, Etain, Bruno, Ferentinos, Panagiotis, Frye, Mark, Fullerton, Janice M., Gawlik, Micha, Gershon, Elliot S., Goes, Fernando S., Green, Melissa J., Grigoroiu-Serbanescu, Maria, Hauser, Joanna, Henskens, Frans, Hillert, Jan, Hong, Kyung Sue, Hougaard, David M., Hultman, Christina M., Hveem, Kristian, Iwata, Nakao, Jablensky, Assen V., Jones, Ian, Jones, Lisa A., Kahn, René S., Kelsoe, John R., Kirov, George, Landén, Mikael, Leboyer, Marion, Lewis, Cathryn M., Li, Qingqin S., Lissowska, Jolanta, Lochner, Christine, Loughland, Carmel, Martin, Nicholas G., Mathews, Carol A., Mayoral, Fermin, McElroy, Susan L., McIntosh, Andrew M., McMahon, Francis J., Melle, Ingrid, Michie, Patricia, Milani, Lili, Mitchell, Philip B., Morken, Gunnar, Mors, Ole, Mortensen, Preben Bo, Mowry, Bryan, Müller-Myhsok, Bertram, Myers, Richard M., Neale, Benjamin M., Nievergelt, Caroline M., Nordentoft, Merete, Nöthen, Markus M., O’Donovan, Michael C., Oedegaard, Ketil J., Olsson, Tomas, Owen, Michael J., Paciga, Sara A., Pantelis, Chris, Pato, Carlos, Pato, Michele T., Patrinos, George P., Perlis, Roy H., Posthuma, Danielle, Ramos-Quiroga, Josep Antoni, Reif, Andreas, Reininghaus, Eva Z., Ribasés, Marta, Rietschel, Marcella, Ripke, Stephan, Rouleau, Guy A., Saito, Takeo, Schall, Ulrich, Schalling, Martin, Schofield, Peter R., Schulze, Thomas G., Scott, Laura J., Scott, Rodney J., Serretti, Alessandro, Shannon Weickert, Cynthia, Smoller, Jordan W., Stefansson, Hreinn, Stefansson, Kari, Stordal, Eystein, Streit, Fabian, Sullivan, Patrick F., Turecki, Gustavo, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Waldman, Irwin D., Weickert, Thomas W., Werge, Thomas, Wray, Naomi R., Zwart, John-Anker, Biernacka, Joanna M., Nurnberger, John I., Cichon, Sven, Edenberg, Howard J., Stahl, Eli A., McQuillin, Andrew, Di Florio, Arianna, Ophoff, Roel A., and Andreassen, Ole A.

Published
2021
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37. Advanced Circadian Phase in Mania and Delayed Circadian Phase in Mixed Mania and Depression Returned to Normal after Treatment of Bipolar Disorder

Author

Moon, Joung-Ho, Cho, Chul-Hyun, Son, Gi Hoon, Geum, Dongho, Chung, Sooyoung, Kim, Hyun, Kang, Seung-Gul, Park, Young-Min, Yoon, Ho-Kyoung, Kim, Leen, Jee, Hee-Jung, An, Hyonggin, Kripke, Daniel F, and Lee, Heon-Jeong

Subjects
Clinical Research, Depression, Mental Health, Serious Mental Illness, Bipolar Disorder, Behavioral and Social Science, Brain Disorders, Sleep Research, Adult, Affect, Age of Onset, Biomarkers, Case-Control Studies, Circadian Rhythm, Exercise, Female, Humans, Hydrocortisone, Male, Saliva, Young Adult, Circadian rhythm, Bipolar disorders, Phase shift, Circadian dysregulation, Clinical Sciences, Public Health and Health Services
Abstract

Disturbances in circadian rhythms have been suggested as a possible cause of bipolar disorder (BD). Included in this study were 31 mood episodes of 26 BD patients, and 18 controls. Circadian rhythms of BD were evaluated at admission, at 2-week intervals during hospitalization, and at discharge. All participants wore wrist actigraphs during the studies. Saliva and buccal cells were obtained at 8:00, 11:00, 15:00, 19:00, and 23:00 for two consecutive days. Collected saliva and buccal cells were used for analysis of the cortisol and gene circadian rhythm, respectively. Circadian rhythms had different phases during acute mood episodes of BD compared to recovered states. In 23 acute manic episodes, circadian phases were ~7hour advanced (equivalent to ~17hour delayed). Phases of 21 out of these 23 cases returned to normal by ~7hour delay along with treatment, but two out of 23 cases returned to normal by ~17hour advance. In three cases of mixed manic episodes, the phases were ~6-7hour delayed. For five cases of depressive episodes, circadian rhythms phases were ~4-5hour delayed. After treatment, circadian phases resembled those of healthy controls. Circadian misalignment due to circadian rhythm phase shifts might be a pathophysiological mechanism of BD.

Published
2016

44. Circadian polymorphisms in night owls, in bipolars, and in non-24-hour sleep cycles.

Author

Kripke, Daniel F, Klimecki, Walter T, Nievergelt, Caroline M, Rex, Katharine M, Murray, Sarah S, Shekhtman, Tatyana, Tranah, Gregory J, Loving, Richard T, Lee, Heon-Jeong, Rhee, Min Kyu, Shadan, Farhad F, Poceta, J Steven, Jamil, Shazia M, Kline, Lawrence E, and Kelsoe, John R

Subjects
BHLHE40, Bipolar disorder, Delayed sleep phase syndrome, NFIL3, Non-24 hour sleep-wake disorder, RORC
Abstract

People called night owls habitually have late bedtimes and late times of arising, sometimes suffering a heritable circadian disturbance called delayed sleep phase syndrome (DSPS). Those with DSPS, those with more severe progressively-late non-24-hour sleep-wake cycles, and those with bipolar disorder may share genetic tendencies for slowed or delayed circadian cycles. We searched for polymorphisms associated with DSPS in a case-control study of DSPS research participants and a separate study of Sleep Center patients undergoing polysomnography. In 45 participants, we resequenced portions of 15 circadian genes to identify unknown polymorphisms that might be associated with DSPS, non-24-hour rhythms, or bipolar comorbidities. We then genotyped single nucleotide polymorphisms (SNPs) in both larger samples, using Illumina Golden Gate assays. Associations of SNPs with the DSPS phenotype and with the morningness-eveningness parametric phenotype were computed for both samples, then combined for meta-analyses. Delayed sleep and "eveningness" were inversely associated with loci in circadian genes NFIL3 (rs2482705) and RORC (rs3828057). A group of haplotypes overlapping BHLHE40 was associated with non-24-hour sleep-wake cycles, and less robustly, with delayed sleep and bipolar disorder (e.g., rs34883305, rs34870629, rs74439275, and rs3750275 were associated with n=37, p=4.58E-09, Bonferroni p=2.95E-06). Bright light and melatonin can palliate circadian disorders, and genetics may clarify the underlying circadian photoperiodic mechanisms. After further replication and identification of the causal polymorphisms, these findings may point to future treatments for DSPS, non-24-hour rhythms, and possibly bipolar disorder or depression.

Published
2014

50. FMR1, circadian genes and depression: suggestive associations or false discovery?

Author

Kripke, Daniel F, Nievergelt, Caroline M, Tranah, Gregory J, Murray, Sarah S, Rex, Katharine M, Grizas, Alexandra P, Hahn, Elizabeth K, Lee, Heon-Jeong, Kelsoe, John R, and Kline, Lawrence E

Abstract

Abstract Background There are several indications that malfunctions of the circadian clock contribute to depression. To search for particular circadian gene polymorphisms associated with depression, diverse polymorphisms were genotyped in two samples covering a range of depressed volunteers and participants with normal mood. Methods Depression mood self-ratings and DNA were collected independently from a sample of patients presenting to a sleep disorders center (1086 of European origin) and from a separate sample consisting of 399 participants claiming delayed sleep phase symptoms and 406 partly-matched controls. A custom Illumina Golden Gate array of 768 selected single nucleotide polymorphisms (SNPs) was assayed in both samples, supplemented by additional SNPlex and Taqman assays, including assay of 41 ancestry-associated markers (AIMs) to control stratification. Results In the Sleep Clinic sample, these assays yielded Bonferroni-significant association with depressed mood in three linked SNPs of the gene FMR1: rs25702 (nominal P=1.77E-05), rs25714 (P=1.83E-05), and rs28900 (P=5.24E-05). This FMR1 association was supported by 8 SNPs with nominal significance and a nominally-significant gene-wise set test. There was no association of depressed mood with FMR1 in the delayed sleep phase case–control sample or in downloaded GWAS data from the GenRED 2 sample contrasting an early-onset recurrent depression sample with controls. No replication was located in other GWAS studies of depression. Our data did weakly replicate a previously-reported association of depression with PPARGC1B rs7732671 (P=0.0235). Suggestive associations not meeting strict criteria for multiple testing and replication were found with GSK3B, NPAS2, RORA, PER3, CRY1, MTNR1A and NR1D1. Notably, 16 SNPs nominally associated with depressed mood (14 in GSK3B) were also nominally associated with delayed sleep phase syndrome (P=3E10-6). Conclusions Considering the inconsistencies between samples and the likelihood that the significant three FMR1 SNPs might be linked to complex polymorphisms more functionally related to depression, large gene resequencing studies may be needed to clarify the import for depression of these circadian genes.

Published
2013

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